Information output method, information output system, and program

Abstract

To provide an information output method capable of reducing the consumption power of an air conditioning system while reducing energy consumption in a building, an information output system, and a program.SOLUTION: A disclosed information output method includes: a duration estimation step of estimating power consumption per unit period of an air conditioning system, or peak period in the time of year when the total power consumption of the entire building equipment, including the air conditioning system, is at its highest per unit time; an area identification step of identifying areas where the heat load during the peak period is higher than in other areas out of each of these areas when a building is divided into multiple areas; an information generation step of identifying an air conditioning unit that controls the air conditioning for the designated area as the target device from among the air conditioning units included in the air conditioning system and generating a piece of air conditioning control information recommending implementing demand control to limit the output of the target device during peak periods; and an output step of outputting the air conditioning control information.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to an information output method, an information output system, and a program. [Background technology]

[0002] Patent Document 1 discloses a technique for controlling air conditioning equipment arranged in each zone of a building so that the demand, which is the building's power demand, does not exceed the maximum demand based on the contracted power. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2012-211732 Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure provides an information output method, an information output system, and a program that enable suppression of power consumption by air conditioning equipment and reduction of energy consumption in buildings. [Means for solving the problem]

[0005] The information output method of the present disclosure is an information output method that outputs information related to the air conditioning equipment of a building by a computer, and includes: a period estimation step that estimates the peak period during which the amount of power consumption per unit period of the air conditioning equipment, or the amount of power consumption per unit period of all the equipment in the building including the air conditioning equipment, is the largest in an year; an area identification step that, when the building is divided into multiple areas, identifies an area among the areas that has a higher heat load during the peak period than the other areas; an information generation step that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the area identified in the area identification step as a target device, and generates air conditioning control information that recommends demand control to limit the output of the target device during the peak period; and an output step that outputs the air conditioning control information.

[0006] The information output method of the present disclosure is an information output method that outputs information regarding the air conditioning equipment of a building by a computer, and includes: an acquisition step of acquiring usage information including the start time of use of the building; a heat load calculation step of calculating the heat load at the start time of use for each of the areas when the building is divided into multiple areas; an area identification step of identifying an area having a higher heat load per unit area at the start time of use than the other areas; an apparatus identification step of identifying, as a target apparatus, an air conditioning apparatus included in the air conditioning equipment that will air condition the identified area; an information generation step of generating air conditioning control information that recommends that the target apparatus perform either a pre-cooling operation that starts cooling operation before the start time of use, or a pre-heating operation that starts heating operation before the start time of use; and an output step of outputting the air conditioning control information.

[0007] The information output method disclosed herein is an information output method that outputs information related to the air conditioning equipment of a building by a computer, and includes an acquisition step of acquiring usage information including the end time of use of the building; an area identification step of identifying, when the building is divided into multiple areas, an area in which the heat load per unit area at the end time of use satisfies a predetermined condition; an apparatus identification step of identifying, as a target apparatus, an air conditioning apparatus included in the air conditioning equipment that performs air conditioning in the identified area; an information generation step of generating air conditioning control information that recommends early stop control for the target apparatus to stop operation before the end time of use; and an output step of outputting the air conditioning control information.

[0008] The information output system of the present disclosure is an information output system that outputs information related to the air conditioning equipment of a building, and includes: a period estimation unit that estimates the peak period during which the amount of power consumption per unit period of the air conditioning equipment or the amount of power consumption per unit period of all the equipment in the building including the air conditioning equipment is the largest in an year; an area identification unit that identifies, when the building is divided into multiple areas, an area that has a higher thermal load during the peak period than the other areas; an information generation unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the area identified by the area identification unit as a target device, and generates air conditioning control information that recommends demand control to limit the output of the target device during the peak period; and an output unit that outputs the air conditioning control information.

[0009] The information output system of the present disclosure is an information output system that outputs information related to the air conditioning equipment of a building, and includes: an acquisition unit that acquires usage information including the start time of use of the building; a heat load calculation unit that calculates the heat load at the start time of use for each of the areas when the building is divided into multiple areas; an area identification unit that identifies an area with a higher heat load per unit area at the start time of use than the other areas; an apparatus identification unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that will perform air conditioning in the identified area as a target device; an information generation unit that generates air conditioning control information that recommends that the target device perform either pre-cooling operation, which starts cooling operation before the start time of use, or pre-heating operation, which starts heating operation before the start time of use; and an output unit that outputs the air conditioning control information.

[0010] The information output system of the present disclosure is an information output system that outputs information related to the air conditioning equipment of a building, and includes: an acquisition unit that acquires usage information including the end time of use of the building; an area identification unit that identifies, when the building is divided into multiple areas, an area in which the thermal load per unit area at the end time of use satisfies specified conditions; an apparatus identification unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that conditions the identified area as a target device; an information generation unit that generates air conditioning control information that recommends early stop control for the target device, which will stop operation before the end time of use; and an output unit that outputs the air conditioning control information.

[0011] The program of the present disclosure is a program that causes a processor that outputs information about the air conditioning equipment of a building to function as: a period estimation unit that estimates the power consumption per unit period of the air conditioning equipment, or the peak period during which the power consumption per unit period of all the equipment in the building, including the air conditioning equipment, is the highest in an year; an area identification unit that identifies, when the building is divided into multiple areas, an area that has a higher thermal load during the peak period than the other areas; an information generation unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the area identified by the area identification unit as a target device, and generates air conditioning control information that recommends demand control to limit the output of the target device during the peak period; and an output unit that outputs the air conditioning control information.

[0012] The program of the present disclosure is a program that causes a processor that outputs information about the air conditioning equipment of a building to function as an acquisition unit that acquires usage information including the start time of use of the building, a heat load calculation unit that calculates the heat load at the start time of use for each of the areas when the building is divided into multiple areas, an area identification unit that identifies an area that has a higher heat load per unit area at the start time of use than the other areas, an apparatus identification unit that identifies, among the air conditioning units included in the air conditioning equipment, the air conditioning unit that will perform air conditioning in the identified area as a target apparatus, an information generation unit that generates air conditioning control information that recommends that the target apparatus perform either pre-cooling operation, which starts air conditioning operation before the start time of use, or pre-heating operation, which starts heating operation before the start time of use, and an output unit that outputs the air conditioning control information.

[0013] The program of the present disclosure is a program that causes a processor that outputs information about a building's air conditioning equipment to function as an acquisition unit that acquires usage information including the end time of use of the building, an area identification unit that identifies, when the building is divided into multiple areas, an area in which the heat load per unit area at the end time of use satisfies specified conditions, an apparatus identification unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that conditions the identified area as a target device, an information generation unit that generates air conditioning control information that recommends early stop control for the target device to stop operation before the end time of use, and an output unit that outputs the air conditioning control information. [Effects of the Invention]

[0014] The information output method, information output system, and program disclosed herein enable a reduction in the energy consumption of a building by outputting information for realizing a reduction in the power consumption of an air conditioning system. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram showing an overview of an information output system according to a first embodiment. [Figure 2] FIG. 1 is an explanatory diagram showing an example of a building to which the first embodiment is applied; [Figure 3] Block diagram of a terminal device according to the first embodiment. [Figure 4] FIG. 10 is a diagram showing an example of the configuration of basic data used by a terminal device according to the first embodiment; [Figure 5] Flowchart showing the operation of the server device in the first embodiment [Figure 6] Flowchart showing the operation of the server device in the first embodiment [Figure 7] FIG. 10 is a diagram showing an example of information output in the first embodiment. [Figure 8] Flowchart showing the operation of the server device in the first embodiment [Figure 9] Flowchart showing the operation of the server device in the first embodiment DETAILED DESCRIPTION OF THE INVENTION

[0016] (Findings that formed the basis of this disclosure) At the time the inventors arrived at the idea of ​​this disclosure, demand control was being performed to suppress peak power consumption of air conditioning equipment based on the building's contracted power. For example, there was a technology that divided the conditioned space of a building into a perimeter zone, which is heavily influenced by the envelope load, and an interior zone, which is heavily influenced by the internal load, and stopped air conditioners corresponding to the perimeter zone first when the difference between the predicted demand value and the maximum demand was small. However, designing and implementing a system capable of controlling a large number of air conditioners installed in a building incurs significant costs. Furthermore, the impact of solar radiation on air conditioning load varies depending on the orientation, season, and time of day of the conditioned space, and indoor heat generation varies depending on factors such as the number of people in the room. In particular, when the building in question is a new construction, or when operating information for the air conditioner, such as power consumption and outside temperature, cannot be collected in an existing building, it is difficult to evaluate and improve the design of the air conditioner, and the inventors discovered that it was difficult to realize a system for efficiently reducing the power consumption of the building's air conditioning equipment.In order to solve this problem, they have come up with the subject matter of the present disclosure. Therefore, the present disclosure provides an information output method, an information output system, and a program that enable suppression of power consumption by air conditioning equipment and reduction of energy consumption in buildings.

[0017] Hereinafter, embodiments will be described in detail with reference to the drawings. However, in some cases, more detailed explanation than necessary may be omitted. For example, detailed explanation of already well-known matters or redundant explanation of substantially the same configuration may be omitted. The accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter described in the claims.

[0018] (Embodiment 1) [1-1. Information output system configuration] FIG. 1 is a diagram showing an overview of an information output system 1000. As shown in FIG.

[0019] The information output system 1000 includes a terminal device 2 and a server device 3, and provides an information provision service related to a building BL. The information provision service includes generating and outputting support information related to an air conditioning apparatus 1 installed in the building BL.

[0020] Examples of building BL include houses, offices, warehouses, stores, factories, schools, and lodgings. In this embodiment, non-residential buildings such as commercial buildings are taken as examples of building BL. The information provision service provided by the information output system 1000 can be applied to both building BL, which is a newly constructed building, and existing building BL. In the following description, the indoor space of the building BL includes rooms used by users in the building BL, shared spaces such as corridors and halls, and other spaces, and these are collectively referred to as "rooms" or "indoor spaces."

[0021] The terminal device 2 is a PC (Personal Computer). In Fig. 1, a laptop PC is illustrated as an example of the terminal device 2, but the terminal device 2 may be a desktop PC, a tablet PC, or a smartphone.

[0022] The server device 3 is a device that processes information using devices connected to the network NW as clients. The network NW includes the Internet, a telephone network, and other communication networks. Although the server device 3 is represented by a single block in FIG. 1, this does not necessarily mean that the server device 3 is composed of a single device. The server device 3 may also be a so-called cloud server.

[0023] The target of the information provision service is a candidate for air conditioning equipment 1 that is scheduled to be installed in a newly constructed building BL. The target of the information provision service may also be a candidate for air conditioning equipment 1 that is scheduled to be installed in an existing building BL when an update of the existing air conditioning equipment is scheduled. The target of the information provision service may also be air conditioning equipment 1 that is installed in an existing building BL. In FIG. 1, the newly constructed building BL1 is indicated by a dotted line, and the existing building BL2 is indicated by a solid line.

[0024] 2 is an explanatory diagram showing an example of a building BL to which support by the information output system 1000 is applied. When the building BL is a newly constructed building, the configuration of the building BL is assumed as shown in FIG. 2 based on the design drawings of the building BL.

[0025] The building BL shown in FIG. 2 has multiple floors FL, specifically floor FL1 with an entrance and floors FL2, FL3, and FL4 above floor FL1. The space of each floor FL constitutes one or more areas AL. For example, floor FL3 is divided into four areas AL. The other floors FL1, FL2, and FL4 may be divided into multiple areas AL like floor FL3, or the entire space of floor FL may be one area AL. Areas AL do not have to be spaces separated by walls or the like; for example, one space may include multiple areas AL. Also, shared spaces such as corridors may be considered one area AL.

[0026] As described above, air conditioners 11 are installed in building BL. In the example of FIG. 2, air conditioner 11A, which conditions floor FL1 as the conditioned space, air conditioner 11B, which conditions floor FL2, air conditioner 11C, which conditions floor FL3, and air conditioner 11D, which conditions floor FL4, are installed. Air conditioner 11A is configured by connecting one outdoor unit 12 and multiple indoor units 13 via a refrigerant circuit 14. For example, the indoor units 13 are installed in each area AL, and each indoor unit 13 cools and heats one area AL. The same is true for air conditioners 11B, 11C, and 11D, which are installed in each area AL on floors FL2 to FL4, and the multiple indoor units 13 are connected to one outdoor unit 12 via the refrigerant circuit 14. The air conditioner 11 may be configured such that the multiple indoor units 13 can individually switch between cooling and heating, or may be configured such that all of the indoor units 13 perform the same operation, either cooling or heating.

[0027] The outdoor units 12 of the air conditioners 11A to 11D are connected to an air conditioning control device 10. The air conditioning control device 10 is a controller that controls the operation of the air conditioners 11 and has a processor and control circuit (not shown), such as a microcontroller. The air conditioning control device 10 has the function of measuring and storing the main power of the building or the power of the power grid that supplies power to the air conditioners 11. This measured power is used to calculate peak power and control demand for the air conditioners 11. Types of power received by buildings that are the subject of the present invention include low voltage, high voltage, and extra high voltage. Buildings are equipped with power receiving equipment such as cubicles and power meters depending on the building's use. Furthermore, within the building, power equipment such as distribution boards and power meters is installed on a floor-by-floor or room-by-room basis depending on the use of the room. The building is also equipped with equipment that can store and utilize the power measured in the building. The air conditioning control device 10 outputs, for example, various control signals to each outdoor unit 12. Each outdoor unit 12 performs demand control and the like in accordance with the control signals input from the air conditioning control device 10.

[0028] The control signal output by the air conditioning control device 10 may be, for example, a control signal instructing the start or stop of demand control, a control signal specifying the set temperature or demand value during demand control, or other control signals. Specifically, when demand control of the air conditioning equipment 1 is being executed, the air conditioning control device 10 outputs a control signal indicating the upper limit of the rotation speed of the compressor (not shown) of the outdoor unit 12, the set temperature of the indoor unit 13, or other control values.

[0029] As shown in FIG. 2, the configuration in which one air conditioner 11 is installed on each floor FL is one example. For example, indoor units 13 installed on multiple floors FL may constitute one air conditioner 11, and the connection relationship between the indoor units 13 and the outdoor units 12 can also be designed appropriately based on the specifications of the building BL. The air conditioner 11 may be, for example, a package air conditioner, a central air conditioner, or a system air conditioner that combines these. Examples of package air conditioners include multi-air conditioners and air conditioners for stores and offices. Examples of multi-air conditioners include electric (EHP) and gas (GHP) types, but other configurations are also possible.

[0030] A ventilation device may be provided in the area AL. The ventilation device may be, for example, a device that supplies and exhausts air between the area AL and the outside, or a device with a heat exchange function. For example, it may be a total heat exchange ventilator (ERV: Energy Recovery Ventilator). It may also be a device with a function to adjust the humidity of the air in the area AL, such as by absorbing moisture, dehumidifying, or humidifying. It may also be an outside air treatment package that introduces outside air into the area AL.

[0031] Below, examples will be described in which the operation modes of the air conditioner 11 include demand control, pre-cooling operation, pre-heating operation, and early stop control. Demand control is an energy-saving measure in which a demand control device automatically controls equipment such as air conditioning and lighting so that the main power of a building does not exceed a predetermined power value. For example, by controlling demand so that the main power of a building that receives high-voltage bulk power does not exceed the contracted power, it is possible to suppress annual peak power. In the case of demand control at low voltage, it is possible to save power from the perspective of reducing power consumption. The demand control, pre-cooling operation, pre-heating operation, and early shutdown control targeted by this invention can be applied not only to buildings that receive high-voltage power, but also to buildings that receive other types of power, such as low voltage or extra-high voltage. Peak power reduction of the outdoor unit is one of the air conditioning control methods among the demand controls executed for the air conditioning equipment 1. This is a control to reduce the peak power of the outdoor unit 12, and is an energy saving measure by limiting the upper limit of the outdoor unit's capacity. The targets of automatic demand control may include limiting the temperature setting of the indoor unit 13 and controlling the illuminance of the lighting in area AL. Demand control of the air conditioner 11 can be achieved using the air conditioning control device 10, but a simpler method of achieving this is to take energy-saving measures by simply suppressing the peak power of the outdoor unit 12 using a controller or the like provided in the air conditioner 11. Using this method also makes it possible to suppress the annual peak power.

[0032] Demand control of the air conditioner 11 is performed, for example, in 30-minute increments. A demand value is used as an index for demand control. The demand value refers to the instantaneous value of the power used by the air conditioner 11, and in operating the air conditioner 11, the demand value is the average power used (unit: kw) over 30 minutes. The largest demand value in a day is called the maximum demand value. When demand control is performed, a control signal instructing the start of demand control is input from the air conditioning control device 10 to the outdoor unit 12. At this time, a control value for demand control may be input from the air conditioning control device 10 to the outdoor unit 12. The control value for demand control is, for example, the demand value, the upper limit of the rotation speed of the compressor of the outdoor unit 12, the upper or lower limit of the set temperature of the indoor unit 13, etc.

[0033] Pre-cooling operation is an operation mode in which, during a period in which the air conditioner 11 performs cooling operation, the air conditioner 11 starts cooling before the start time of use of the building BL or area AL. The start time of use is, for example, the start time of business for a company or organization located in the building BL. If pre-cooling operation is not performed, the operation of the air conditioner 11 is concentrated around the start time of use, and the power consumption of the air conditioner 11 peaks immediately after starting operation. If pre-cooling operation is performed to avoid peak concentration, operating the air conditioner 11 before the start time of use improves indoor comfort at the start time of use and reduces the heat load of the area AL at the start time of use, thereby suppressing the peak power consumption of the air conditioner 11. Similarly, during a period in which the air conditioner 11 performs heating operation, starting heating by the air conditioning equipment 1 before the start time of use of the building BL can suppress the peak power consumption of the air conditioner 11.

[0034] Early stop control is an operation mode in which cooling or heating by the air conditioner 11 is stopped before the end of use time of building BL. The end of use time is, for example, the end of business time of a company or organization occupying building BL. If the air conditioner 11 is stopped before the end of use time so that the indoor temperature of area AL at the end of use time is within an appropriate range, it is possible to reduce power consumption by shortening the operating time of the air conditioner 11 while maintaining comfort in area AL.

[0035] [1-2. Overview of the operation of the information output system] Here, an overview of the operation of the information output system 1000 will be described. The building BL that is the target of the service provided by the information output system 1000 is an existing building or a newly constructed building.

[0036] If the building BL is an existing building, the information output system 1000 generates and outputs recommendation data 224 including information about air conditioning equipment 1 to be installed in the already constructed building BL to replace the existing air conditioning equipment. If the building BL is a new building, the information output system 1000 generates and outputs recommendation data 224 including information about air conditioning equipment 1 to be installed in the building BL that is currently under construction or is scheduled to be constructed.

[0037] First, the conditions are selected for the air conditioner 11. When a newly constructed building BL is the target, the heat load of each area AL is calculated using the design drawings of the building BL. Specifically, first, calculation conditions such as the wall conditions of the building BL (materials and thicknesses of the exterior walls, interior walls, floors, roofs, and windows, and heat transmission coefficients), outdoor temperature, solar radiation load, etc. are input. Next, the wall load is calculated based on the indoor and outdoor temperature conditions of each area AL of the building BL. Then, the capacity and type of the air conditioner 11 that matches the calculation result of the heat load are selected as the conditions for the air conditioner 11.

[0038] The process is generally similar when targeting an existing building BL. That is, the thermal load of each area AL of the building BL is calculated using the design drawings of the building BL as well as the results of a field survey of the building BL. Then, the conditions of the air conditioner 11 that match the calculated thermal load are selected.

[0039] Next, detailed model selection of air conditioners 11 that meet the selected conditions is performed, for example, using catalog data for the air conditioners 11. For example, first, the models of the outdoor units 12 and indoor units 13 of each system of the air conditioners 11 and the indoor units 13 of each area AL are selected. A system of the air conditioners 11 is a structural unit consisting of one outdoor unit 12 and the indoor units 13 connected to this outdoor unit 12 via a refrigerant circuit 14. As the indoor units 13, equipment with a capacity that matches the heat load of the area AL, specifically equipment with a capacity equal to or greater than the heat load of the area AL, is selected. Next, an outdoor unit 12 with a capacity equal to or greater than the total cooling and heating capacity of the indoor units 13 in the system is tentatively selected. Here, the capacities of the outdoor units 12 and the indoor units 13 are corrected. Correction items include correction of the intake temperature of the indoor unit 13, correction of the intake temperature of the outdoor unit 12, defrost correction, and correction based on the refrigerant piping length of the refrigerant circuit 14 and the difference in elevation between the inside and outside of the refrigerant piping. In addition, a margin value for equipment capacity correction may be set by the designer selecting the air conditioning equipment 1. Thereafter, the total value of the corrected capacities of the indoor units 13 in the system is calculated, and if the corrected capacity of the outdoor unit 12 is the same as or greater than the total value of the capacities of the indoor units 13, the provisional selection is completed, but if it is less than the total value of the capacities of the indoor units 13, the outdoor unit 12 is reselected.

[0040] There are no limitations on the device that selects the air conditioner 11. For example, the selection may be performed by the terminal device 2, the server device 3, or a device other than the information output system 1000. Furthermore, when selecting the air conditioner 11, a ventilation device that matches the ventilation volume required for each area AL may be selected.

[0041] For the air conditioner 11 selected in this way, the information output system 1000 uses an energy simulator to estimate the effect of demand control of the air conditioner 11 and the effect of having the air conditioner 11 perform pre-cooling operation or pre-heating operation. The information output system 1000 then generates and outputs recommendation data 224 including the estimation results. By introducing an energy simulator, it becomes easier to evaluate and improve the design of the air conditioner, even when targeting a newly constructed building or when information related to air conditioner operation, such as power consumption and outside temperature, has not been collected in an existing building.

[0042] After the air conditioner 11 has been selected, the requester P2 provides basic data D1 including information about the selected air conditioner 11 to the operator P1 who operates the terminal device 2. As will be described later, the basic data D1 includes information about the building BL, information about the area where the building BL is located, information about the use of the area AL of the building BL and information about the equipment installed in the area AL, information about the operating time and set temperature of the air conditioning equipment 1, etc.

[0043] An operator P1 inputs basic data D1 into a terminal device 2. Furthermore, if the terminal device 2 is capable of acquiring the basic data D1 from the server device 3, the operator P1 operates the terminal device 2 to acquire the basic data D1. The terminal device 2 uses the basic data D1 to execute an information output process for an information provision service.

[0044] When requested by a client P2, the operator P1 uses the terminal device 2 to output recommendation data 224 for the selected air conditioning equipment 1. Here, the operator P1 may be a person who selects the air conditioning equipment 1, a person who manages the air conditioning equipment 1, or a person who provides consulting on the air conditioning equipment 1. The operator P1 may also be a person who constructed or designed the building BL. The client P2 may be, for example, the owner of the building BL or a person who has been requested by the owner to manage the building BL. Furthermore, the terminal device 2 may generate the operation data 225 by the operator P1 using the terminal device 2.

[0045] The recommendation data 224 and operation data 225 generated by the terminal device 2 will be described. The recommended data 224 and the operational data 225 include information relating to the introduction or use of the air conditioners 11 that make up the air conditioning equipment 1. The recommended data 224 is information about the air conditioner 11 that the operator P1 presents to the client P2 or other persons in order to provide information about the air conditioner 11. The information included in the recommended data 224 is displayed by the terminal device 2 or other devices, such as an information display screen 31 described below.

[0046] The operational data 225 is data that can be used to control the air conditioner 11. The operational data 225 is output from the terminal device 2 to the air conditioning control device 10 or other devices, and is used by these devices. The operational data 225 is, for example, data for operating the air conditioner 11 in a manner recommended in the recommendation data 224. By inputting the operational data 225 to the air conditioner 11, or by the air conditioning control device 10 controlling the air conditioner 11 in accordance with the operational data 225, the operation presented in the recommendation data 224 can be realized. The recommendation data 224 and the operational data 225 are examples of "air conditioning control information."

[0047] For example, the recommendation data 224 includes content that recommends that control be executed to reduce power consumption by the air conditioning equipment 1. Specifically, the recommendation data 224 includes content that recommends that demand control be executed by the air conditioning equipment 1. In this case, the recommendation data 224 includes content that explains the timing for executing demand control, the time period for demand control, the effects of executing demand control, etc.

[0048] Furthermore, the recommendation data 224 includes, for example, content that recommends that the air conditioning apparatus 1 perform pre-cooling operation or pre-heating operation. Furthermore, the recommendation data 224 includes, for example, content that recommends that early shutdown control of the air conditioning equipment 1 be executed.

[0049] Demand control, pre-cooling operation, pre-heating operation, and early stop control are performed for an area AL of the building BL that is identified by processing described below. Specifically, demand control, pre-cooling operation, pre-heating operation, and early stop control are performed by the indoor unit 13 that conditions the identified area AL and the outdoor unit 12 connected to this indoor unit 13. In this embodiment, an example is described in which demand control, pre-cooling operation, pre-heating operation, and early stop control are performed by control of the air conditioning control device 10, but these controls may also be performed by operating a remote control installed in the area AL.

[0050] [1-3. Terminal Device Configuration] FIG. 3 is a block diagram of the terminal device 2 according to the first embodiment. As shown in FIG. 3, the terminal device 2 includes a control device 20, a communication unit 21, a display 22, and an input unit 23.

[0051] The control device 20 is a device that controls each part of the terminal device 2. The control device 20 includes a processor 200 such as a CPU (Central Processing Unit) or an MPU (Micro Processor Unit), a memory 220, and an interface circuit. Note that other devices and sensors included in the terminal device 2 are connected to this interface circuit.

[0052] The memory 220 is a memory that stores programs and data. The memory 220 stores a program 221, simulation model data 222, recommendation data 224, and operation data 225. The memory 220 stores, for example, basic data D1 acquired by the terminal device 2 as data to be processed by the processor 200. The memory 220 has a non-volatile storage area. The memory 220 also has a volatile storage area and constitutes a work area for the processor 200. The memory 220 is constituted, for example, by a ROM (Read Only Memory) or a RAM (Random Access Memory).

[0053] The processor 200 includes, as functional units, an acquisition unit 201, a period estimation unit 202, an identification unit 203, an information generation unit 204, and an output unit 205. The processor 200 also includes a simulator 210 and a prediction unit 215. These functional units are realized by the processor 200 executing a program 221.

[0054] The acquisition unit 201 acquires information used to generate the recommended data 224 and the operational data 225. Specifically, the acquisition unit 201 acquires the basic data D1 and stores it in the memory 220.

[0055] The period estimation unit 202 estimates a period during which the building BL will have high power consumption based on the basic data D1. More specifically, the period estimation unit 202 estimates, for a planned period, a period during which the power consumption per unit period of the air conditioning equipment 1 or the power consumption per unit period of all the equipment in the building BL, including the air conditioning equipment 1, will be maximum. The planned period and unit period can be set arbitrarily, and the planned period is longer than the unit period. For example, the planned period can be one year, six months, three months, one month, etc., and the unit period can be one minute, one hour, 12 hours, 24 hours, etc. In this embodiment, the planned period is one year, and the unit period is one day. The period estimated by the period estimation unit 202 is a peak period. The peak period can be set to any length, such as one day, half a day, one hour, 30 minutes, etc. In this embodiment, the period estimation unit 202 estimates the day in a year when the power consumption of the air conditioning equipment 1 or the power consumption of all the equipment in the building BL including the air conditioning equipment 1 is the greatest, and determines the peak period to be the hour or 30 minutes on the estimated day when the power consumption per unit period is the greatest.

[0056] The period estimation unit 202 acquires information on the amount of solar radiation of the building BL during the planning period from the information acquired by the acquisition unit 201, and estimates a peak period so that it overlaps with the day on which the amount of solar radiation is the highest in a year. For example, the peak period is one hour or 30 minutes on the day on which the amount of solar radiation is the highest in a year.

[0057] Furthermore, the period estimation unit 202 sets the estimated base date to either the hottest day or the coldest day of the year in the area where the building BL is installed, or the next usage day following consecutive non-usage days in the usage schedule of the building BL. The period estimation unit 202 estimates the peak period so that it overlaps with the day on which the power consumption of the air conditioning equipment 1 is at its maximum within a predetermined range from the estimated base date. Non-usage days are non-working days for companies, etc. that use the building BL, such as Saturdays, Sundays, national holidays, and other holidays. Usage days are business days for companies, etc. that use the building BL.

[0058] The identifying unit 203 identifies the air conditioner 11 with the highest air conditioning load in the building BL. Here, the air conditioning load can be rephrased as the thermal load of the area AL that is air-conditioned by the air conditioner 11. The identifying unit 203 estimates the thermal load of each area AL in the building BL using the simulator 210, and identifies the area AL with the high thermal load. The identifying unit 203 may identify one or more areas AL. For example, the identifying unit 203 identifies one or more areas AL with a higher thermal load than other areas AL. Then, the identifying unit 203 identifies the air conditioner 11 that conditions the area AL with the high thermal load. The identifying unit 203 is an example of an "area identifying unit" and an "equipment identifying unit." Note that, as a method for identifying an area AL with a high thermal load, a method may be used in which the thermal load per unit area is compared for each area AL, rather than just the total amount of the area's thermal load. Furthermore, even if an area AL has a high thermal load, if the area AL is used as a room where deterioration of the thermal environment due to demand control would be a problem (e.g., a hospital room, a server room, etc.), it may be excluded from demand control.

[0059] The information generation unit 204 generates recommendation data 224 and operation data 225 related to the target device, with the air conditioner 11 identified by the identification unit 203 as the target device. For example, the information generation unit 204 generates information related to demand control, pre-cooling operation, pre-heating operation, and early stop control of the target device during peak periods. The information generation unit 204 generates recommendation data 224 and operation data 225 including the generated information. The information generation unit 204 may aggregate the information generated for each air conditioner 11 included in the air conditioning equipment 1 to generate recommendation data 224 and operation data 225 corresponding to the air conditioning equipment 1.

[0060] The output unit 205 outputs the recommended data 224 and the operational data 225. The output mode of the output unit 205 is not limited. For example, the output unit 205 displays the contents of the recommended data 224 on the display 22. As one output mode, the output unit 205 may transmit the recommended data 224 to a device other than the terminal device 2. As one output mode, the output unit 205 may cause a printer to print the recommended data 224.

[0061] There are no limitations on the manner in which the output unit 205 outputs the operation data 225. For example, the output unit 205 transmits the operation data 225 to the server device 3 or another device. The output unit 205 may also store the operation data 225 on a portable recording medium. The output unit 205 may also transmit the operation data 225 to the air conditioning control device 10.

[0062] The simulator 210 uses an energy simulator program to create a simulation model 211 based on the simulation model data 222. The simulator 210 executes a simulation by providing parameters included in the basic data D1 to the simulation model 211, and obtains the execution results. The simulator 210 can generate a simulation model 211 according to the type and content of the simulation to be executed, and can also create multiple simulation models 211.

[0063] For example, a simulation model such as EnergyPlus, TRNSYS, or BEST is used as the simulation model 211. The simulation model 211 may be configured such that a plurality of models are configured as one simulation model and one simulation is executed.

[0064] The simulation model 211 includes a building model, a weather model, a solar radiation model, an air conditioning and ventilation equipment model, and an operation model of the air conditioning and ventilation. A building model is defined by the structural information of the building, such as the exterior walls, floors, roofs, and interior walls of the building BL. The structural information includes, for example, material, thickness, and heat transmittance. The information used to define the building model is obtained, for example, from the design drawings of the building BL provided by the designer or contractor who designed the building BL. If the building BL is an existing building, the information used to define the building model is obtained from the design drawings and management drawings of the building BL provided by the manager or owner of the building BL.

[0065] The weather model and solar radiation model are defined by meteorological information such as temperature, humidity, and solar radiation in the area where building BL is located. The weather model simulates the outside temperature of building BL. The solar radiation model simulates the effect of solar radiation on building BL. The weather data used in the weather model and solar radiation model is data provided by organizations and companies that provide weather information, such as extended AMeDAS weather data. Furthermore, if building BL is an existing building, sensors are installed in building BL, and the detected values ​​of these sensors can be obtained, the detected values ​​of these sensors can be used in either or both of the weather model and solar radiation model. For example, the detected values ​​of an outside air temperature sensor, a solar radiation sensor, and temperature and humidity sensors installed inside building BL may be used in the weather model and solar radiation model.

[0066] The air conditioning and ventilation equipment model is a model that defines the equipment operation of the air conditioner 11. The air conditioning and ventilation equipment model is defined by the operation mode (cooling, heating), set temperature, air volume, operation period, operation time, rated COP, rated power consumption, etc. of the air conditioner 11. The air conditioning and ventilation equipment model executes an energy simulation of the air conditioner 11, and the power consumption, etc. of the air conditioner 11 are obtained from the simulation results. The air conditioning and ventilation equipment model may also be a model that defines the equipment operation of a ventilation device that is installed in area AL together with the air conditioner 11. In this case, the air conditioning and ventilation equipment model is defined by information such as the operation mode, rated air volume, operation period, operation time, etc. of the ventilation device, and the power consumption, etc. of the ventilation device are obtained from the simulation results. Furthermore, by providing the control value of demand control to the air conditioning and ventilation equipment model, it is possible to obtain the power consumption of the air conditioner 11 when demand control is executed and an appropriate demand value.

[0067] The operation model included in the simulation model 211 performs a simulation of the operation of building BL. The operation model calculates the heat generation due to an increase or decrease in the number of people, the heat generation due to lighting, the heat generation due to equipment, and the heat generation due to the introduction of outside air through ventilation. The operation model may include, for example, a human body heat generation model, a lighting equipment heat generation model, and other equipment heat generation models, or may be an operation model that integrates these. It may also include a model that calculates the heat generation due to the introduction of outside air. The human body heat generation model is defined by the number of people, a reference value for human body heat generation per person, a human body heat generation ratio schedule, etc., and calculates the heat generation of people in area AL. It is desirable that the human body heat generation model be able to calculate the sensible heat component and the latent heat component separately. The lighting equipment heat generation model is defined by the type of lighting equipment, the number of lighting equipment, the rated power of the lighting equipment, the lighting heat generation ratio schedule, etc., and calculates the heat generation of lighting devices in area AL. The equipment heat generation model is defined by the number and power consumption of equipment such as office automation equipment, the equipment heat generation ratio schedule, etc., and calculates the heat generation of equipment in area AL. The human heat generation ratio schedule, lighting heat generation ratio schedule, and equipment heat generation ratio schedule can be, for example, the default values ​​of WEBPRO. If building BL is an existing building, the power consumption of lighting devices and other equipment may be calculated from the actual power consumption of building BL. Similarly, the human heat generation ratio schedule, lighting heat generation ratio schedule, and equipment heat generation ratio schedule may be calculated based on the usage history of existing building BL, and these may be applied to the human heat generation model, lighting equipment heat generation model, and other equipment heat generation model. Furthermore, the model of the heat load of area AL due to the introduction of outside air can be, for example, the ventilation schedule, which is the default value of WEBPRO. If building BL is an existing building, the human heat generation ratio schedule, lighting heat generation ratio schedule, and equipment heat generation ratio schedule can be created using power history analysis based on the actual measured power consumption of building BL. In this case, for the existing building BL, the start and end times of use, the number of users, and entry and exit history of the entire building BL or each area AL may be used, and changes in occupancy by time period may be estimated from this information.

[0068] Furthermore, the simulator 210 generates a simulation model 211 according to the intended use of the building BL and the area AL. For example, a building model, a weather model, a solar radiation model, a human body heat generation model, a heat generation model of lighting equipment, and an air conditioning and ventilation equipment model of the air conditioner 11 are generated for various buildings BL. If the building BL is used as an office, the simulator 210 generates a heat generation model of office equipment. Furthermore, for example, if the building BL includes an area AL used as a store, the simulation model 211 includes a heat generation model of kitchen equipment and an air conditioning and ventilation equipment model of a ventilation fan and a range hood. The kitchen equipment heat generation model includes a heat generation model of sensible heat emitted by the kitchen equipment and a model of latent heat generation due to steam from the kitchen equipment. Furthermore, for example, if the building BL includes an area AL used as a restaurant, the simulation model 211 includes a heat generation model of kitchen equipment, a heat generation model of water heaters, and an air conditioning and ventilation equipment model of ventilation equipment such as a ventilation fan and a range hood. The heat generation model of the water heater, like the heat generation model of kitchen equipment, includes a heat generation model of sensible heat emitted by the water heater and a model of latent heat generation due to steam from the water heater.

[0069] Here, a method for calculating power consumption and heat load (amount of cooling, amount of heating) using an air conditioning and ventilation equipment model (air conditioning and ventilation equipment model of the air conditioner 11) will be described. The air conditioning and ventilation equipment model is given parameters such as the set temperature, set air volume, rated COP, and rated power consumption for each operation mode of the air conditioner 11.

[0070] The air conditioning and ventilation equipment model is composed of the following equations (1) to (4). Q = F(ΔT1) (1) Q = ρ × Cp × Vol × ΔT2 (2) Load factor = Q ÷ rated capacity of outdoor unit (3) Power consumption = Q÷COP (4) In equations (1) to (4), Q is the amount of cooling when the air conditioner is cooling, and the amount of heating when the air conditioner is heating. In equation (1), F() is calculated by looking up Q in a table corresponding to ΔT1. The value of Q calculated using F() is a table showing the relationship between ΔT1 and Q, created based on the minimum, rated, and maximum capacities of the selected model. Specifically, the table is created with reference to the specifications, configuration, and control logic of the actual air conditioner. In equation (1), ΔT1 is the difference between the set temperature and the sensor value, and the sensor value is the intake temperature of the indoor unit. If the indoor unit can detect floor temperature, the difference between the set temperature and the floor temperature may be used instead of the intake temperature. In equation (2), ΔT2 is the difference between the supply air temperature and the sensor value. During heating, it is the supply air temperature minus the sensor value, and during cooling, it is the sensor value minus the supply air temperature. In equation (2), ρ is the density of air, Cp is the specific heat of air, and Vol is the supply air volume, which is a constant value.

[0071] The air conditioning and ventilation equipment model performs calculations (1) to (4), and returns to calculation (1) once calculation (4) is complete. First, Q is calculated using equation (1). In calculating Q using equation (1), ΔT1 is calculated based on information obtained from the air conditioner's operating data, and the capacity corresponding to ΔT1 is set as Q. Next, Q calculated using equation (1) is substituted into equation (2) to calculate the supply air temperature that constitutes ΔT2. Q calculated using equation (1) is substituted into the left side of equation (3) to calculate the load factor. Next, the COP corresponding to the load factor calculated using equation (3) is calculated from the relationship diagram between the load factor and COP. Then, Q calculated using equation (1) and the COP calculated are substituted into equation (4), and the left side of equation (4) is calculated as the power consumption corresponding to the current load factor. The characteristics of the relationship between load factor and COP are defined for each air conditioner model, and the relationship between load factor and COP is determined by specifying the rated COP and rated power consumption of the air conditioner in the air conditioning and ventilation equipment model. The relationship between load factor and COP can also be determined separately for cooling and heating. Other simulation conditions that are given to the air conditioning and ventilation equipment model include the operating mode (cooling, heating, dehumidification), set temperature, and set airflow.

[0072] Here, an example of creating a table showing the relationship between ΔT1 and Q will be described. The air conditioning load Q that the air conditioner must process includes heat entering the room from the walls, floor, and ceiling (transmission heat), radiant heat (solar radiation, long-wave radiation), and internal heat generation (from people, lighting, and equipment). Radiant heat, including solar radiation, can be assumed to be absorbed by one of the solid surfaces in the room, so it can be included in the transmission heat. When measuring the floor temperature with the indoor unit 13, the infrared array sensor installed in the indoor unit 13 can measure not only the floor temperature but also the floor temperature, including internal heat generation (heat generation from people and equipment in the room), and these can be reflected in the control of the air conditioner.

[0073] To simplify table design, one method is to calculate the air conditioning load Q that an air conditioner must process using transverse heat. According to this method, the air conditioning load Q, which is transverse heat, can be calculated using the formula Q = α × A × ΔT1. Here, α is the indoor convection heat transfer coefficient, and is either a function of wind speed or a general fixed value for the indoor side. A is the total surface area of ​​the room (walls, floor, and ceiling). A is defined based on the standard room size assumed for the hardware capacity of the indoor unit 13 (air conditioner specifications). A is defined as an air conditioner model by creating a table showing the relationship between ΔT1 and Q from the transverse heat equation while changing the magnitude of ΔT1.

[0074] The prediction unit 215 generates a prediction model 216 from the simulation results of the simulator 210. The prediction unit 215 may have a plurality of prediction models 216. The prediction unit 215 of this embodiment has a model that predicts the annual maximum peak power for demand control, which will be described later, and a model that predicts the required time for pre-cooling operation and pre-heating operation, which will be described later. The prediction model 216 is an example of a "computation model."

[0075] The demand control prediction model 216 outputs a predicted value of annual peak power when an outdoor temperature is given. The prediction unit 215 generates the prediction model 216 by performing a regression analysis of the correlation between annual peak power and outdoor temperature. Specifically, a simulator is used to calculate a predicted value of annual peak power using time-series data of outdoor temperatures at the location provided by the Japan Meteorological Agency or the like. Furthermore, time-series data of outdoor temperatures from multiple years is used to calculate a large number of outdoor temperatures and peak power. Furthermore, to increase the amount of data, simulation results for a building near the location may be used. Additionally, time-series data of outdoor temperatures in an area slightly distant from the location may be used. Furthermore, the outdoor temperature may be measured using a sensor installed in the air conditioner or a temperature sensor installed separately from the air conditioner. In this case, the simulation conditions may be distinguished by the building's use (e.g., office, store, etc.) and operation mode (e.g., air conditioner operating hours), and the results of simulations performed for each building use or operation mode may be used.

[0076] The prediction model 216 has a correlation between the outdoor temperature of a specific building BL or a specific area AL in the building BL and the annual peak power or the peak power in summer or winter. The prediction model 216 is expressed, for example, by the following formula (5).

[0077] Annual peak power (predicted value) = Outdoor temperature × PA + PB (5) In equation (5), PA and PB are parameters determined by the prediction unit 215.

[0078] In addition to the regression analysis, the prediction unit 215 also generates a prediction model 216 as a trained model by having AI (Artificial Intelligence), such as machine learning and reinforcement learning, learn learning data that shows the correlation between annual peak power and outside temperature.

[0079] By using the prediction model 216, it is possible to obtain a predicted value of the annual peak power of the air conditioner 11 based on the outside temperature obtained from the weather forecast for the area where the building BL is located. The setting value for demand control can be determined using this annual peak power (predicted value) using a method described below.

[0080] The prediction unit 215 obtains simulation results regarding changes in power consumption of the air conditioner 11 or the outdoor unit 12 over a year using, for example, the simulator 210. Here, the simulation model 211 uses the building model, air conditioning and ventilation equipment model, operation model, and solar radiation model, as well as weather data obtained from the Japan Meteorological Agency and the like. The prediction unit 215 also obtains data on the annual peak power consumption of the outdoor unit 12 and outdoor temperature data for the area where the building BL is located. The outdoor temperature data is included, for example, in the weather data 44 described below. The prediction unit 215 may use the acquired data divided into days when the building BL is used and days when it is not used to generate the prediction model 216. For example, the prediction unit 215 may use demand value data separately for weekdays, holidays (including public holidays), or an annual calendar of days when the building BL is used. Furthermore, when an existing building BL is the target, a highly accurate prediction model may be created by creating long-term data using actual past power consumption values ​​of the air conditioner 11 or the outdoor unit 12 and values ​​representing future power consumption values ​​as simulation results.

[0081] The prediction model 216 for pre-cooling / pre-heating operation predicts the time required for pre-cooling operation and pre-heating operation when calculation conditions are given. This prediction model 216 may include a model for pre-cooling operation and a model for pre-heating operation. The prediction unit 215, for example, uses the simulator 210 to obtain simulation results of changes in the indoor temperature in area AL for each operating time of the air conditioner 11 when pre-cooling operation is performed in area AL. Here, the building model, air conditioning and ventilation equipment model, operation model, and solar radiation model of the simulation model 211, as well as weather data obtained from the Japan Meteorological Agency and the like, are used. The prediction unit 215 may obtain simulation results for the number of operating outdoor units 12 and the model and type of indoor units 13.

[0082] The prediction unit 215 generates a prediction model 216 that predicts the time for pre-cooling and pre-heating operation by performing a regression analysis based on the simulation results of the simulator 210. The calculation conditions given to the prediction model 216 include the intake temperature (indoor temperature) of the indoor unit 13 at the start of operation, the set temperature of the indoor unit 13, the outdoor air temperature at the start of use, the outdoor air temperature at the start of operation, and the number of operating outdoor units 12. The prediction unit 215 generates the prediction model 216 by performing a regression analysis of the correlation between these calculation conditions and the time required for the indoor temperature of area AL to be brought within a predetermined range from the set temperature through pre-cooling operation.

[0083] The prediction model 216 generated in this way is expressed by, for example, the following equations (6) to (8).

[0084] Indoor temperature difference = outside temperature difference × PP + PPP (6) Time required for pre-cooling and pre-heating = indoor temperature difference × PQ + PQQ (7) Power consumed for pre-cooling and pre-heating = Time required for pre-cooling and pre-heating × PR + PRR (8)

[0085] In equations (6) to (8), PP, PPP, PQ, PQQ, PR, and PRR are parameters determined by the prediction unit 215. These parameters are determined by regression analysis. The indoor temperature difference is calculated as the difference between the intake temperature (indoor temperature) of the indoor unit 13 at the start of operation and the set temperature. Specifically, this can be calculated using the operating data of the air conditioner model in the simulator. The outdoor temperature difference is calculated as the difference between the outdoor temperature at the start of use and the outdoor temperature at the start of operation. Specifically, this can be calculated using time series data of past outdoor temperatures for the location obtained from the Japan Meteorological Agency, etc. The time required for pre-cooling and pre-heating is the time for operating the air conditioner 11 before the start time of use in area AL, and is the difference between the start time of operation of the air conditioner 11 and the start time of use. Specifically, this can be calculated using the operating data of the air conditioner model in the simulator. When taking into account the number of operating outdoor units 12, a term related to the number of operating units is added to relational expression (7) and the calculation is performed using regression analysis. Note that the number of operating outdoor units 12 can be calculated using the operating data of the air conditioning and ventilation equipment model in the simulation. In this example, it is assumed that the operating mode (cooling or heating) of the air conditioner 11, the airflow rate and set temperature of the indoor unit 13, and the number of operating outdoor units 12 are fixed during the pre-cooling and pre-heating period.

[0086] Next, we will describe an example of how to calculate the above relationship equations (6) to (8) using the operating data of the simulator's air conditioner model. Assuming a start time of use (e.g., 7:00 AM), a set temperature (heating, set to 20°C, automatic airflow), and a start time of pre-cooling / pre-heating (e.g., 90 minutes before the set start time of use), we run the simulator to calculate the intake temperature (room temperature) of the indoor unit 13 at the start of operation, the room temperature at the start time of use, and the power consumption of the air conditioner 11 required for pre-cooling / pre-heating operation. If the difference between the room temperature at the start time of use calculated by the simulator and the set temperature is small (e.g., 0.5°C or less), this data is used for regression analysis calculations. Furthermore, data to be used for regression analysis is created in the same manner by fixing the start time of use and the set temperature and varying the start time of pre-cooling / pre-heating. Additionally, the start time of use and the set temperature are also varied to create operating data under numerous simulation conditions. Using the operating data created by the simulator, the parameters of equations (6) to (8) are identified through regression analysis. It should be noted that the formulas (6) to (8) may be constructed for each use start time and set temperature.

[0087] To calculate the time required for pre-cooling and pre-heating of an actual air conditioner 11 using the above relational expression, for example, a user of the air conditioner 11 sets the start time and set temperature of the air conditioner 11 in advance on the air conditioner 11 device itself or on the controller. The prediction process involves assuming multiple pre-cooling and pre-heating start times (e.g., 60, 90, and 120 minutes before the set start time), and using forecasted (or actual) time-series outdoor temperature data for the location obtained from the Japan Meteorological Agency or other sources, calculating the outdoor temperature difference between the assumed pre-cooling and pre-heating start time and the start time of use. The indoor temperature difference is calculated from the obtained outdoor temperature difference using relational expression (6). The time required for pre-cooling and pre-heating is calculated from the indoor temperature difference between the start time and the start time of use obtained by the simulator using relational expression (7). Then, power consumption is calculated from the time required for pre-cooling and pre-heating using relational expression (8), and the start time of pre-cooling and pre-heating with the lowest power consumption can be selected from the multiple assumed start times. The operation start time and set temperature thus determined are reflected in the device body, controller, etc. of the air conditioner 11 to realize pre-cooling and pre-heating.

[0088] The terminal device 2 may generate a prediction model corresponding to the pre-cooling operation and a prediction model corresponding to the pre-heating operation as the prediction models represented by equations (6) to (8). Furthermore, the prediction unit 215 may use the above calculation conditions and the operating data of the air conditioner model under simulation conditions in which the indoor temperature at the start of use of area AL is within a predetermined range from the set temperature through pre-cooling / pre-heating operation as learning data in the same manner as described above, and use this data for machine learning to generate the prediction model 216 as a trained model. In this case, for example, the set temperature, the start time of pre-cooling / pre-heating, the start time of use, the indoor temperature, the outdoor temperature, the power consumed by pre-cooling / pre-heating, the number of operating outdoor units, etc. are given as explanatory variables, and a trained model is created in which the time required for pre-cooling / pre-heating is used as the objective variable.

[0089] The simulator 210 and the prediction unit 215 are not limited to being implemented in the terminal device 2, and may be implemented in the server device 3 or other devices that can communicate with the terminal device 2. For example, the prediction unit 215 may be implemented in the device body or controller of the air conditioner 11, or the simulator 210 and the prediction unit 215 may be implemented in a cloud server. In this case, when the terminal device 2 needs a simulation by the simulator 210 or a prediction by the prediction unit 215, it can obtain the simulation results or the predicted values ​​by the prediction model 216 by communicating with the other device.

[0090] The communication unit 21 includes communication hardware such as a communication circuit conforming to a predetermined communication standard, and communicates with each device connected to the network NW.

[0091] The display 22 is configured with elements such as liquid crystal, LED (Light Emitting Diode), OLED (Organic LED), etc. The display 22 displays various information under the control of the control device 20.

[0092] The input unit 23 includes an interface circuit that connects to devices such as operation switches, a touch input panel, a mouse, and a keyboard, detects input operations by the operator P1, and outputs the detection results to the processor 200.

[0093] [1-4. Data used in the information output system] The data used in the information output system 1000 will be described. FIG. 4 is a diagram showing an example of the configuration of the basic data D1.

[0094] 4, the basic data D1 includes building data 42, weather data 44, air conditioning device data 45, plan data 47, and existing building data 48. These data are used when generating the simulation model 211.

[0095] The building data 42 includes information about the building BL, and this information can be obtained, for example, from blueprints of the building BL. The building data 42 includes the location of the building BL, the number of floors FL, the number of areas AL, their orientation, and the uses of the areas AL. The building data 42 may also include the floor area and opening area of ​​the areas AL. The building data 42 may also include operation data. The operation data is data related to the operation of the building BL. For example, the operation data of the building data 42 includes the use time of the building BL, a use schedule (planned use), entry and exit data, etc. The use time data may include the start time and end time of use, or may be data for each day of the week. The use schedule is data that can distinguish between days when the building BL is used (use days) and days when it is not used (non-use days) over a period of one year, six months, etc. The entry and exit data may include the entry time and exit time for each person, or may be an average or median.

[0096] The building data 42 may include staffing ratio data. The staffing ratio data is a reference value common to multiple areas of the building BL or a value corresponding to a specific area AL. For example, the building data 42 may include staffing ratio data for each area AL. The staffing ratio data is, for example, information indicating changes in staffing ratios in the area AL by time period. If the building BL is a new construction, the staffing ratio data may be determined based on interviews with the client or construction company staff, actual values ​​in buildings similar to the building BL, or literature. Information regarding the number and density of people prepared for ventilation design may be used as the staffing ratio data. Furthermore, information regarding changes in staffing ratios over time as defined in energy conservation standards may be used as the staffing ratio data. For example, the staffing ratio data may be information regarding staffing ratios for each room use as defined in WEBPRO. The staffing ratio data can be used when the simulation model 211 calculates the thermal load in the area AL using an operation model. The staffing ratio data may be included in the operation data described above. The staffing ratio data is an example of "staffing information."

[0097] The weather data 44 is data related to the weather in the area including the location of building BL, such as data from the Extended AMeDAS. The weather data 44 includes, for example, annual temperature data corresponding to the outside temperature of building BL. The weather data 44 may also include the hottest day and the coldest day. The hottest day refers to the hottest day in a year in the location of building BL, specifically the day with the highest temperature in a year. The coldest day refers to the coldest day in a year in the location of building BL, specifically the day with the lowest temperature in a year. With regard to the hottest day and the coldest day, "temperature" refers to one or more of the maximum temperature of a day, the minimum temperature of a day, the sum of the maximum and minimum temperatures of a day, and the average temperature of a day, or temperatures obtained by other statistical processing.

[0098] The air conditioning device data 45 includes data related to the air conditioner 11. The air conditioning device data 45 is data associated with one type of air conditioner 11, and air conditioning device data 45 is prepared for each model number and type of air conditioner 11. The air conditioning device data 45 includes, for example, data related to the rated power consumption and cooling and heating capacities of the air conditioner 11. The air conditioning device data 45 is used when generating an air conditioner model of the air conditioner 11. The air conditioning device data 45 may also include data related to a ventilation device installed in area AL together with the air conditioner 11.

[0099] The planning data 47 includes information about the air conditioning equipment 1 to be installed in the building BL. Specifically, it includes information about the selected air conditioner 11, such as the model of the selected air conditioner 11, the number and placement of the indoor units 13 and outdoor units 12, etc. The planning data 47 is used in the air conditioning and ventilation equipment model and building model of the building BL. The planning data 47 may include data about the ventilation device.

[0100] The existing building data 48 is data related to an existing building. The existing building data 48 may include data related to an existing building, such as the building data 42, weather data 44, and air conditioning device data 45, or may include data added to these data. Examples of added data include the outdoor temperature, indoor temperature, power consumption, number of people, and human density measured in an existing building. If the building BL is an existing building and actual measured data exists for the building BL, that data is stored in the existing building data 48. The existing building data 48 may also be data related to a building different from the building BL. The existing building data 48 may include, for example, data related to an existing building located near the building BL or an existing building with similar conditions to the building BL. In this case, when the information output system 1000 executes a service for the building BL, which is a newly constructed building, the existing building data 48 related to the other building can be reused.

[0101] [1-4. Operation] 5, 6, 8, and 9 are flowcharts showing the operation of the terminal device 2. FIG. 7 is an example of information output by the terminal device 2. The operation of the terminal device 2 in this embodiment will be described with reference to these figures. The operation of the terminal device 2 shown in each figure is executed by the processor 200. These operations are realized by, for example, the simulator 210 or the program 221 that functions as a front end of the simulator 210.

[0102] [1-4-1. Demand control operations] 5 and 6 show the operation of outputting the recommendation data 224 and operation data 225 related to demand control. Details of step S11 in FIG.

[0103] 5, step S11 is executed by the acquisition unit 201 and the period estimation unit 202, and steps S12-S14 are executed by the identification unit 203. Steps S15-S17 are executed by the information generation unit 204, and step S20 is executed by the output unit 205.

[0104] The terminal device 2 estimates the peak period (step S11). 6 shows an example of the operation of step S11. The terminal device 2 acquires the building data 42 and the weather data 44 (step S31). The terminal device 2 identifies the hottest day, a predetermined number of days before and after the hottest day, the coldest day, and a predetermined number of days before and after the coldest day based on data such as location and direction included in the building data 42 and annual temperature data included in the weather data 44 (step S32). If the terminal device 2 outputs the recommendation data 224 and the operation data 225 only for cooling operation of the air conditioning equipment 1, the processing related to the coldest day may be omitted in step S32.

[0105] The terminal device 2 acquires information about the usage schedule of the building BL from the building data 42, and identifies the next usage date after consecutive non-usage dates of the building BL (step S33). The next usage date after consecutive non-usage dates is, in other words, the usage date after a consecutive holiday (e.g., after a summer vacation or a winter vacation). The terminal device 2 determines the date identified in steps S32 and S33 as the estimated reference date (step S34).

[0106] The terminal device 2 estimates the peak power value of the entire building BL on the estimated reference date (step S35). The peak power value is the power consumption during the time period when power consumption is highest in a day (for example, 13:00 to 14:30). The terminal device 2 estimates the power consumption of the entire building BL on the estimated reference date in units of one hour, 30 minutes, one minute, etc., and calculates the peak power value.

[0107] In step S35, for example, the terminal device 2 uses the simulator 210. The terminal device 2 calculates the heat load of each area AL of the building BL using the building model, weather model, and solar radiation model of the simulator 210. Here, the amount of heat generated inside the area AL may be calculated based on the indoor heat generation model of the simulator 210 and added to the heat load of the area AL. Based on the heat load of the area AL, the terminal device 2 calculates the power consumption of the air conditioning equipment 1 for a certain period before and after the estimated reference date using the air conditioning and ventilation equipment model of the acquisition unit 201, and estimates the peak power value from the calculated power consumption. Here, if the simulation model 211 includes models of equipment other than the air conditioning equipment 1, this model may be used to calculate the power consumption of equipment other than the air conditioning equipment 1 in the building BL and add it to the power consumption of the air conditioning equipment 1.

[0108] In step S35, the terminal device 2 estimates a peak power value for each of a plurality of estimated reference days. The terminal device 2 identifies the day on which the peak power value is maximum among the estimated reference days (step S36). In step S36, the terminal device 2 may identify one day on which the peak power value is maximum, or may identify multiple days including the day on which the peak power value is maximum. Here, we have explained an efficient calculation method for determining annual peak power by using a simulator to calculate power consumption for a certain period before and after the estimated reference date (for example, one week or one month; if one day is used, the estimated reference date). By simulating a certain period before and after the estimated reference date, we can expect to be able to determine the impact of the thermal storage capacity of building BL. Another way to calculate peak power is to calculate power consumption for one year and then calculate the annual peak power. This has the advantage of being able to calculate all peak power that occurs on days other than the estimated reference date and evaluate the magnitude of the peak power. It is also possible to calculate power consumption for each season, summer and winter, and then determine the peak power for each season to perform demand control. This has the advantage of being able to distinguish between seasons for which demand control is set.

[0109] The terminal device 2 may use the simulator 210 to calculate the power consumption of the building BL for a predetermined period including the estimated reference date, and estimate the peak power value and the day on which the peak power value will be maximum. For example, the terminal device 2 may use the simulator 210 to calculate the power consumption of the building BL for the entire period of one year. The terminal device 2 may calculate the peak power value from the calculated power consumption for the entire period. Furthermore, the peak power value calculated based on the estimated reference date in steps S32-S36 and the power consumption for the entire period may be stored in the memory 220 in association with each other.

[0110] The terminal device 2 determines, as a peak period, a time period during which the power consumption of the building BL reaches a peak power value on the day identified in step S36 (step S37).

[0111] Returning to FIG. 5, the terminal device 2 performs a process of identifying high-load areas from among the areas AL included in the building BL (step S12). A high-load area refers to an area AL in the building BL that has a high thermal load. A high-load area is an area that has a higher thermal load than at least one other area AL. For example, a predetermined number of areas AL of the building BL can be designated as high-load areas in descending order of thermal load.

[0112] In the process of identifying high-load areas, the terminal device 2 identifies the hottest day and the coldest day, for example, in the same manner as in step S32. The terminal device 2 calculates the heat load on the hottest day and the heat load on the coldest day of each area AL included in the building BL to be processed. The calculated heat load here is, for example, the heat load for the entire area AL, and includes heat generated by people, heat generated by lighting devices, and heat generated by other devices. The terminal device 2 may calculate the heat load for the area AL using an indoor heat generation model of the simulator 210. Then, the terminal device 2 compares the heat loads of multiple areas AL and identifies a predetermined number of areas AL with the highest heat loads as high-load areas.

[0113] The terminal device 2 identifies the air conditioner 11 that will condition the high-load area (step S13). The terminal device 2 identifies the indoor unit 13 that will condition the high-load area, identifies the outdoor unit 12 connected to the indoor unit 13 via the refrigerant circuit 14, and identifies the air conditioner 11 that includes the indoor unit 13 and the outdoor unit 12. The terminal device 2 determines the identified air conditioner 11 and outdoor unit 12 as targets for demand control (step S14). This makes it possible to narrow down the number of outdoor units 12 that will be subjected to demand control. When a demand control device is introduced into the main power supply of building BL, the number of air conditioners 11 that will be controlled can be reduced, which is expected to reduce construction and operation costs. The terminal device 2 determines the time period for which demand control will be performed and the set value for the demand control (step S15). The time period for which demand control will be performed can be, for example, the peak period estimated in step S11. The set value for demand control is, for example, a demand value. For example, the terminal device 2 can determine the demand value based on the contracted power of the building BL and the peak power value of the building BL. The terminal device 2 may also determine the demand value based on the prediction model 216. That is, the terminal device 2 may generate the prediction model 216 that determines the demand value from the outside air temperature, and determine the demand value as a set value using the prediction model 216.

[0114] The set value for demand control may also be a value expressed as a percentage of the capacity limit of the air conditioner 11. Capacity limit refers to control that limits the upper limit of the rotation speed (frequency) of the compressor of the outdoor unit 12 during the period in which demand control is performed. The set value for demand control may also be the upper limit of the rotation speed of the compressor of the outdoor unit 12, the amount of change, upper or lower limit, of the set temperature of the indoor unit 13, a change to the fan mode, a change in air volume, etc.

[0115] An example of a process for determining the upper limit of the rotation speed of the compressor of the outdoor unit 12 as a setting value will be described below. For example, the setting value when demand control is performed during peak periods during cooling operation can be determined by the following formula (9). In the following formula (9), the percentage of the upper limit of the rotation speed of the compressor during demand control relative to the rated rotation speed of the compressor of the outdoor unit 12 is A [%], the integrated value of the power consumption of the outdoor unit 12 during peak periods is PWR(PEAK) [kW], and the rated power consumption of the outdoor unit 12 during cooling operation is P(R) [kW]. The upper limit of the rotation speed of the compressor may be determined by multiplying A by a power saving rate (for example, a 20% reduction). A=PWR(PEAK) / PWR(R)×100 (9)

[0116] The terminal device 2 generates comparison data by comparing the power consumption when demand control is performed using the setting value determined in step S15 with the power consumption when demand control is not performed (step S16). The terminal device 2 generates recommendation data 224 and operation data 225 including the comparison data generated in step S16 (step S17) and outputs them (step S18).

[0117] Step S11 in FIG. 4 is an example of a "period estimation step", step S12 is an example of an "area identification step", steps S13-S17 are an example of an "information generation step", and step S18 is an example of an "output step".

[0118] FIG. 7 is a diagram showing an example of information output in the first embodiment, showing a state in which the terminal device 2 displays the recommended data 224.

[0119] The information display screen 31 is a screen that the terminal device 2 displays on the display 22 based on the recommendation data 224. The information display screen 31 includes a recommendation message 32, a content explanation display 33, and comparison data 34 and 35.

[0120] The recommendation message 32 is a message recommending that demand control be performed. The content explanation display 33 includes text and charts explaining the conditions for the recommended demand control. The comparison data 34 is a chart showing a comparison of the indoor temperature in area AL during one day when demand control is performed and when demand control is not performed, and shows the change in indoor temperature during one day on the hottest day or the coldest day. In addition, the comparison data 35 may include a chart showing a comparison of the change in power consumption of the air conditioning equipment 1 during demand control and when demand control is not performed. The comparison data 35 may also be a chart comparing the power consumption of the air conditioner 11 or outdoor unit 12 that is the target of demand control.

[0121] Using the comparison data 34 and 35, the operator P1 and the client P2 can easily confirm the effect that the presence or absence of demand control has on the room temperature of the area AL, which is the space to be conditioned, and the state of reduction in power consumption.

[0122] The information display screen 31 in Figure 7 is one example. For example, the information display screen 31 may include a chart or the like showing the power consumption of multiple devices along with the presence or absence of demand control. Furthermore, for example, the information display screen 31 may include a chart or text comparing the power consumption and room temperature of multiple air conditioning devices 1 that are candidates for installation in the building BL.

[0123] The information display screen 31 may also include a chart or the like comparing the maximum power consumption over one year. That is, the recommendation data 224 and the operation data 225 may be data comparing the power consumption over one year when demand control is applied and when it is not applied. For example, the terminal device 2 may estimate a first power, which is the maximum power consumption over one year when the air conditioner 11 is operated with demand control applied, and may estimate a second power, which is the maximum power consumption over one year when the air conditioner 11 is operated without demand control applied. In this case, data including the results of comparing the first power and the second power is generated as the recommendation data 224 and the operation data 225.

[0124] [1-4-2. Preparatory operation operations] 8 shows the operation of outputting the recommendation data 224 and operation data 225 related to the preparatory operation. The preparatory operation is a collective term for the pre-cooling operation and the pre-heating operation.

[0125] 8, step S41 is executed by the acquisition unit 201, steps S42-S44 are executed by the identification unit 203, steps S45-S48 are executed by the information generation unit 204, and step S49 is executed by the output unit 205.

[0126] The terminal device 2 acquires building data 42, area data 43, weather data 44, and air conditioning device data 45 (step S41). The terminal device 2 selects an area AL where the load will increase due to solar radiation at a predetermined time including the start time of use (step S42). In step S42, the terminal device 2 uses, for example, a building model and a solar radiation model of the simulator 210. The terminal device 2 calculates the heat load of each area AL before and after the start time of use and the amount of solar radiation given to the area AL, and can select an area AL where the heat load will increase due to the influence of solar radiation before and after the start time of use.

[0127] In step S42, the heat load of area AL around the start time of use on a specific day in a year may be calculated by simulation. In addition, in order to reflect the effect of the heat storage capacity of building BL, the terminal device 2 may perform simulation on the specific day of interest and the period immediately before that, about one week to one month before that day, around the start time of use. Furthermore, the terminal device 2 may apply an indoor heat generation model in the process of calculating the heat load of the area AL to take into account the influence of heat generation inside the area AL.

[0128] The area where the load increases due to solar radiation differs depending on whether the air conditioning equipment 1 is operating in cooling mode or in heating mode. When the air conditioning equipment 1 is operating in cooling mode, solar radiation increases the heat load in area AL, which is susceptible to solar radiation. In contrast, when the air conditioning equipment 1 is operating in heating mode, the heat load in area AL, which is susceptible to solar radiation, decreases. For this reason, it is preferable that the terminal device 2 executes the operation shown in FIG. 8 when the air conditioning equipment 1 is operating in cooling mode and when it is operating in heating mode. Therefore, the following explanation will be given taking the case where pre-cooling operation is performed in the summer when cooling mode is used as an example.

[0129] Furthermore, in step S42, the terminal device 2 may estimate the area AL that is susceptible to solar radiation from the building-related data of the building BL. Specifically, the terminal device 2 may select the area AL that is susceptible to solar radiation based on the direction, the amount of solar radiation, and the opening area of ​​the area data 43.

[0130] The terminal device 2 identifies, from among the areas AL selected in step S42, areas AL whose cooling load in summer is greater than the other areas AL as preliminary operation areas (step S43). The number of preliminary operation areas may be one or more. The preliminary operation areas are, for example, a predetermined number of areas AL extracted in descending order of air conditioning load. Next, the terminal device 2 identifies the air conditioner 11 for which the preliminary operation area is the space to be conditioned (step S44).

[0131] The terminal device 2 determines the preliminary operation time of the air conditioner 11 identified in step S44 (step S45). In step S45, the preliminary operation time may be determined for each indoor unit 13. There are two examples of the operation in step S45. As a first example, the terminal device 2 sets multiple pre-operation times for performing pre-cooling operation. The pre-operation times are set in units of, for example, 1 hour, 30 minutes, or 10 minutes. The terminal device 2 appropriately sets multiple candidate pre-operation times. The terminal device 2 estimates the load at the start of use when performing pre-cooling operation for each set pre-operation time and for each pre-operation area. This load estimation is performed by simulating the heat load of area AL using the building model, air conditioning and ventilation equipment model, and indoor heat generation model of the operation model of the simulator 210. Here, the terminal device 2 preferably targets periods or days with high air conditioning loads. For example, it is sufficient to estimate the air conditioning load at the start of use on the hottest day. The terminal device 2 may identify the hottest day by processing similar to step S32, or may identify the hottest day by referring to the weather data 44.

[0132] Furthermore, the terminal device 2 estimates the power consumption of the air conditioning equipment 1 at the usage start time for each set preliminary operation time. Specifically, the terminal device 2 estimates the power consumption by applying the heat load of the area AL at the usage start time to the air conditioning ventilation equipment model. Then, the terminal device 2 selects a case in which the indoor temperature in the area AL at the start time of use is within a predetermined range from the set temperature, the power consumption at the start time of use is small, and the preparatory operation time is short. Here, the preparatory operation time selected by the terminal device 2 can be said to be an efficient preparatory operation time.

[0133] In other words, an efficient preparatory operation time is, for example, a time when the load at the start of use is low and the power consumption during the preparatory operation time is small. The longer the preparatory operation time, the lower the load at the start of use. However, if the preparatory operation time exceeds a certain length, a saturation state will be reached where the air conditioning load does not decrease even if the preparatory operation time is extended. The preparatory operation time that reaches this saturation state, or the longest preparatory operation time that is shorter than the saturation state, can be called an efficient preparatory operation time.

[0134] As a second example, the terminal device 2 uses the prediction model 216 shown in the above formulas (6) to (8). The terminal device 2 obtains the pre-operation time by providing the conditions for the pre-operation area to the prediction model 216 for the pre-cooling operation generated by the prediction unit 215. The conditions provided to the prediction model 216 are the outdoor air temperature difference, the indoor temperature difference, and the number of operating outdoor units 12, as described above. The terminal device 2 may verify the pre-operation time obtained in the second example. Specifically, when performing pre-cooling operation using the pre-operation time obtained in the second example, the terminal device 2 may determine whether the indoor temperature of the area AL at the start of use is within a predetermined range from the set temperature. The indoor temperature of the area AL at the start of use can be obtained, for example, by the simulation model 211.

[0135] When performing pre-cooling operation for the preliminary operation time specified in step S48, the terminal device 2 eliminates overlaps in the preliminary operation times in multiple areas AL (step S49). That is, when performing pre-cooling operation for the preliminary operation time specified in step S48, the terminal device 2 determines that there is an overlap in the preliminary operation times if the difference in the start times of the pre-cooling operation in multiple areas AL or air conditioners 11 is equal to or less than a predetermined value.

[0136] If there is an overlap of preparatory operation times, the terminal device 2, for example, requests the operator P1 to select whether or not to resolve the overlap. Specifically, the terminal device 2 displays a message on the display 22 requesting the operator to select whether or not to resolve the overlap, and waits for input from the input unit 23. The terminal device 2 resolves the preparatory operation times based on the information input from the input unit 23. For example, the terminal device 2 changes the preparatory operation times for multiple areas AL where the preparatory operation times overlap, so as to minimize the overlap of the preparatory operation times.

[0137] Furthermore, for example, if the total rated power consumption of the outdoor units 12 whose preliminary operation periods overlap does not exceed the predicted annual peak power, the terminal device 2 may notify the operator P1 of this. The predicted annual peak power is calculated, for example, in the same manner as in the process of step S35. The notification can be made, for example, by displaying a notification message on the display 22. The notification message is, for example, a message informing the operator that the annual peak power will not be exceeded even if multiple outdoor units 12 are started simultaneously. If the total rated power consumption of the outdoor units 12 whose preliminary operation periods overlap exceeds the predicted annual peak power, the terminal device 2 requests the operator P1 to select whether or not to resolve the overlap, as described above.

[0138] Furthermore, for example, the terminal device 2 may perform processing to disable the pre-cooling operation in part of the area AL where the pre-operation times overlap. Specifically, the terminal device 2 disables the pre-cooling operation for the indoor units 13 connected to the outdoor units 12 with small capacities among the outdoor units 12 where the pre-operation times overlap. Alternatively, the terminal device 2 disables the pre-cooling operation for the indoor units 13 with short pre-operation times. Furthermore, the indoor units 13 installed in the area AL in the building BL for room uses where air conditioning is highly required (for example, a server room or a hospital room) may be set not to disable the pre-cooling operation.

[0139] The terminal device 2 generates comparison data comparing the results when pre-cooling operation is performed with those when it is not performed (step S47). The comparison data generated in step S47 is, for example, data comparing the indoor temperature change in the preliminary operation area, the change in power consumption of the air conditioner 11 that conditions the preliminary operation area, and the change in power consumption of the air conditioning equipment 1 when pre-cooling operation is performed with those when it is not performed. In addition, comfort indices such as humidity and a discomfort index may be included. These data can be obtained using the simulation model 211. The terminal device 2 generates recommendation data 224 and operation data 225 including the comparison data (step S48) and outputs them (step S49).

[0140] The recommendation data 224 output in step S49 can be, for example, in the same form as the information display screen 31. Specifically, the recommendation data 224 displays information such as text or images recommending pre-cooling operation, the air conditioner 11 to be subjected to pre-cooling operation, the time period suitable for pre-cooling operation, and the days suitable for pre-cooling operation. The recommendation data 224 may also include graphs or tables showing comparative data between cases where pre-cooling operation is performed and cases where pre-cooling operation is not performed.

[0141] Although the pre-cooling operation has been exemplified in the above explanation, the terminal device 2 can similarly perform the processing of FIG. 8 for the pre-heating operation.

[0142] Furthermore, if the air conditioning equipment 1 includes a ventilation device, the terminal device 2 may generate the recommendation data 224 and the operation data 225 by taking into account the impact of ventilation by the air conditioning equipment 1. For example, in seasons when air conditioning is performed by the air conditioner 11, the indoor temperature of the area AL can be lowered by nighttime ventilation, taking advantage of the fact that the outdoor temperature drops at night. Therefore, in an area AL used during the day, ventilation for a predetermined period after the end of use of the area AL can reduce the heat load of the area AL at the start of use the next day. The terminal device 2 estimates the change in the outdoor temperature of the building BL over the course of a day using the building model, weather model, weather data, etc. of the simulation model 211. The outdoor temperature simulation may assume summer or the hottest day.

[0143] Next, the terminal device 2 estimates the heat load at the end of use of the area AL if ventilation is performed between the end of use of the area AL and the start of use of the area the next day. If the estimated heat load is lower than the heat load if ventilation is not performed, the terminal device 2 generates recommendation data 224 and operation data 225 that include a recommendation for pre-cooling operation and nighttime ventilation.

[0144] On the other hand, in seasons when the air conditioner 11 performs heating, the low outdoor temperature increases the heat load in the area AL due to ventilation. In such cases, the terminal device 2 may generate recommendation data 224 and operation data 225 that recommend stopping the ventilation device while performing pre-heating operation. Since the density of people in the area AL is low while performing pre-cooling operation or pre-heating operation, there is little need for ventilation. Therefore, stopping the ventilation device may reduce the air conditioning load caused by outside air and enable more effective pre-heating operation. In such cases, it is advantageous to generate recommendation data 224 and operation data 225 that recommend stopping the ventilation device.

[0145] 8 is an example of an “acquisition step,” and steps S42-S43 are an example of an “area identification step,” step S44 is an example of an “device identification step,” steps S45-S48 are an example of an “information generation step,” and step S49 is an example of an “output step.”

[0146] [1-4-3. Early stopping control operation] FIG. 9 shows the operation of outputting recommendation data 224 and operation data 225 related to early stopping control. 9, step S61 is executed by the acquisition unit 201, steps S62-S63 are executed by the identification unit 203, steps S64-S67 are executed by the information generation unit 204, and step S68 is executed by the output unit 205.

[0147] The terminal device 2 acquires the building data 42, the area data 43, the weather data 44, and the air conditioning device data 45 (step S61). The terminal device 2 selects an area AL whose load will be reduced by solar radiation at the end of use of the area AL (step S62). In step S62, the terminal device 2 uses, for example, a building model and a solar radiation model of the simulator 210. The terminal device 2 calculates the heat load of each area AL and the amount of solar radiation applied to the area AL for a predetermined time before the end of use, and can select the area AL whose heat load will be reduced by the influence of solar radiation at the end of use. In step S62, the terminal device 2 may calculate the heat load of the area AL before the end of use on a specific day in a year by simulation. Furthermore, in order to reflect the effect of the thermal storage capacity of the building BL, the terminal device 2 may simulate the specific day of interest and the period immediately before the end of use, approximately one week to one month prior to that day. Furthermore, the terminal device 2 may apply an indoor heat generation model in the process of calculating the heat load of the area AL to take into account the influence of heat generation inside the area AL.

[0148] The area where the load is reduced by solar radiation differs depending on whether the air conditioning equipment 1 is in cooling operation or heating operation. For this reason, it is preferable that the terminal device 2 executes the operation shown in Fig. 9 when the air conditioning equipment 1 is in cooling operation and when it is in heating operation. Therefore, the following description will be given using as an example a case where early shutdown control is performed in winter when heating operation is performed.

[0149] Furthermore, in step S62, the terminal device 2 may estimate the area AL that is susceptible to solar radiation from the building-related data of the building BL. Specifically, the terminal device 2 may select the area AL that is susceptible to solar radiation based on the direction, the amount of solar radiation, and the opening area of ​​the area data 43.

[0150] The terminal device 2 identifies, from among the areas AL selected in step S62, areas AL having a smaller heating load in winter than other areas AL as early termination areas (step S63). The number of early termination areas may be one or more. The early termination areas are, for example, a predetermined number of areas AL extracted in ascending order of air conditioning load. For example, from among the areas AL of the building BL, the terminal device 2 identifies areas AL having a smaller heat load per unit area during cooling than other areas AL, or areas AL having a larger heat load per unit area during heating than other areas AL. Next, the terminal device 2 identifies the air conditioner 11 that has the early end area as the space to be conditioned (step S64).

[0151] The terminal device 2 determines the early termination time (step S65). The early termination time is the time by which the air conditioner 11 is stopped earlier than the usage end time, and is determined in units of, for example, 1 hour, 30 minutes, or 10 minutes. In step S65, the terminal device 2 appropriately sets multiple candidate early termination times. The terminal device 2 appropriately sets multiple candidate early termination times. The terminal device 2 estimates the load at the usage end time when early termination is performed for each set early termination time and each early termination area. This load estimation can be performed using the simulation model 211 of the simulator 210. Here, the terminal device 2 preferably targets periods or days with high air conditioning loads. For example, the terminal device 2 estimates the room temperature at the usage end time on the coldest day. The terminal device 2 may identify the coldest day by processing similar to step S32, or may identify the coldest day by referring to the weather data 44.

[0152] The terminal device 2 calculates the daily power consumption when early shutdown control is performed as the power consumption of the entire building BL or the power consumption of the air conditioner 11 that is subject to early shutdown control. The terminal device 2 then determines an efficient early shutdown time from among multiple candidate early shutdown times. The terminal device 2 determines the early shutdown time for each area AL, for example. An efficient early shutdown time is, for example, one in which the difference between the room temperature in area AL and the air conditioning set temperature at the time of use termination is small and the early shutdown time is long. While a longer early shutdown time can reduce power consumption, it is expected that the room temperature will more likely deviate from the air conditioning set temperature. However, if the early shutdown time is shorter than a certain length, a saturation state will be reached in which the difference between the room temperature and the air conditioning set temperature will not increase significantly (for example, by more than 2°C) even if the early shutdown time is extended. The early shutdown time that results in this saturation state, or the shortest early shutdown time that is longer than the saturation state, can be referred to as an efficient early shutdown time. It is possible to construct a prediction model for the early termination time using the same concept as pre-cooling / pre-heating control. Specifically, in the same manner as above, a trained model may be generated by using machine learning to learn the operating data of an air conditioner model under simulation conditions in which the indoor temperature at the end of use of area AL is within a predetermined range of the set temperature due to early shutdown control. For example, the set temperature, early shutdown time, end of use time, indoor temperature, outdoor temperature, power consumed by early shutdown control, and the number of operating outdoor units are given as explanatory variables to create a trained model with the early shutdown time as the objective variable. The trained model may be implemented in the air conditioner itself or its controller, or on a cloud server. This makes it possible to predict the early shutdown time without using a simulator. As another method of generating a prediction model, a regression equation may be constructed using these variables using the same concept as pre-cooling / pre-heating control to predict the early shutdown time.

[0153] In step S65, the operation end times of each air conditioner 11 and each indoor unit 13 when early stop control is performed are determined.

[0154] The terminal device 2 generates comparison data comparing the case where early stopping control is performed and the case where early stopping control is not performed for the early termination area (step S66). The terminal device 2 generates recommendation data 224 and operation data 225 including the comparison data (step S67) and outputs them (step S68).

[0155] In step S67, the terminal device 2 generates comparison data that compares, for example, the room temperature in area AL and the power consumption of the air conditioning equipment 1 when early shutdown control is performed and when it is not performed. The terminal device 2 can use the air conditioning and ventilation equipment model of the simulation model 211 to calculate the power consumption of the air conditioning equipment 1.

[0156] The recommendation data 224 generated in step S67 can be in the same form as, for example, the information display screen 31. Specifically, the information display screen 31 displays information such as text or images recommending early stop control, the air conditioner 11 to be subjected to early stop control operation, and time periods and days suitable for early stop control. The information display screen 31 may also include graphs or tables showing comparative data on the room temperature at the time use ends and the power consumption of the air conditioner 11 when early stop control is performed and when early stop control is not performed. In addition, comfort indices such as humidity and a discomfort index may also be included.

[0157] In step S68, the terminal device 2 may output the operation data 225 to the server device 3, the air conditioning control device 10, or another device. For example, the air conditioning control device 10 can execute early shutdown control of the air conditioning equipment 1 by outputting a control signal to the outdoor unit 12 based on the operation data 225. Since the early shutdown control is initiated during the usage time of the building BL, it may be executed by controlling the outdoor unit 12 or by operating a remote control (not shown) provided in the area AL. In other words, a user of the area AL may manually execute the early shutdown control. In this case, the air conditioning control device 10 may assist the user based on the operation data 225 to easily operate the early shutdown control. For example, the remote control may be used to easily select an early shutdown control pattern. An early shutdown control pattern is a combination of execution conditions for early shutdown control, such as the time from the start of early shutdown control to the end of usage and changes to the air conditioning temperature setting before executing early shutdown control. If the conditions for executing early stop control can be easily selected by operating the remote control under the control of the air conditioning control device 10, there is an advantage that early stop control can be easily executed as needed at the discretion of the user of area AL.

[0158] Step S61 in FIG. 9 is an example of an "acquisition step", steps S62-S63 are an example of an "area specification step", steps S64-S67 are an example of an "information generation step", and step S68 is an example of an "output step".

[0159] [1-5. Effects, etc.] As described above, the information output method executed by the information output system 1000 of this embodiment is an information output method that outputs information related to the air conditioning equipment 1 of the building BL using a computer. This information output method includes a period estimation step of estimating the peak period during which the power consumption per unit period of the air conditioning equipment 1 or the power consumption per unit period of all the equipment in the building BL, including the air conditioning equipment 1, is at its highest annually. It also includes an area identification step of, when dividing the building BL into multiple areas AL, identifying an area AL whose heat load during the peak period is higher than that of the other areas AL. It also includes an information generation step of identifying, as a target device, the air conditioners 11 that perform air conditioning in the area AL identified in the area identification step, among the air conditioners 11 included in the air conditioning equipment 1, and generating air conditioning control information that recommends demand control to limit the output of the target device during the peak period. It also includes an output step of outputting the air conditioning control information.

[0160] According to this, information recommending demand control for area AL in building BL where heat load is high is output as recommendation data 224 and operation data 225 as air conditioning control information. By recommending demand control during peak periods when power consumption by the air conditioning equipment 1 in building BL is high, it is possible to effectively suppress the power consumption of the air conditioning equipment 1 in building BL. Therefore, it is possible to suppress the power consumption of the air conditioning equipment 1 and reduce the energy consumption of building BL.

[0161] The information output method includes a heat load calculation step of calculating the heat load during the peak period estimated in the period estimation step for each area AL of the building BL. In an area identification step, an area AL having a higher heat load during the peak period than other areas AL is identified from among multiple areas AL of the building BL.

[0162] According to this, by performing the process of calculating the heat load of the area AL, it is possible to appropriately identify the area AL for which the effect of demand control is large from among the multiple areas AL included in the building BL.

[0163] In the information output method, the estimated reference date is either the hottest day or the coldest day of the year in the area where the building BL is installed, or the next usage day after consecutive non-usage days in the usage schedule of the building BL in the period estimation step. In the period estimation step, the peak period is estimated so as to overlap with the day on which the power consumption of the air conditioning equipment 1 is at its maximum within a predetermined range from the estimated reference date.

[0164] This makes it possible to identify areas AL with high thermal loads by targeting days in a year when the air conditioning load of the air conditioning equipment 1 in building BL is particularly high. Therefore, it is possible to identify areas AL where great effects can be obtained through demand control, and it is also possible to efficiently identify areas AL with high thermal loads.

[0165] In the information generation step, the information output method predicts the power consumption of the target device during peak periods, and generates recommendation data 224 and operation data 225, including information related to demand control of the target air conditioner 11, based on the ratio between the integrated value of the predicted power consumption and the rated power consumption of the target device. Note that the information on the outside temperature used in this method and the peak power obtained by simulation may also be used to create a peak power prediction model.

[0166] According to this, for example, by using the above formula (1), it is possible to appropriately determine the set value of the demand control, and to realize more effective demand control.

[0167] In the information generation step, the information output method generates a prediction model 216 that estimates the integrated value of the power consumption of the target device from the outside air temperature based on at least data on the annual power consumption of the target device and data on the annual outside air temperature, and generates information related to demand control by providing a predicted value of the outside air temperature to the prediction model 216.

[0168] According to this, by using the prediction model 216, the power consumption of the target device can be easily calculated from the forecast value of the outside temperature obtained from the weather forecast, etc. Furthermore, the prediction model 216 can be generated by regression analysis or AI machine learning using the simulation results of the simulation model 211, and a highly accurate prediction model 216 can be obtained by such methods. Furthermore, by creating a prediction model using the simulation results, it is possible to create a prediction model even when the target is a newly constructed building or when information such as power consumption and outside temperature has not been collected for an existing building. Furthermore, by creating a prediction model according to the characteristics of the building, such as the building use and location, and applying it to various projects, it is possible to reduce the number of simulations performed for each project.

[0169] In the information output method, in the information generation step, a first operation mode in which the target device is operated with demand control applied and a second operation mode in which the target device is operated without demand control are set. Then, the indoor temperature on at least one of the hottest day and the coldest day of the year in the area where the building BL is installed is estimated for each of the first operation mode and the second operation mode. Then, recommendation data 224 and operation data 225 including information comparing the indoor temperatures estimated for each of the first operation mode and the second operation mode are generated and output.

[0170] This makes it possible to generate and output recommendation data 224 and operational data 225 that compare the difference in power consumption of the air conditioner 11 with and without demand control.

[0171] In the information output method, in the information generating step, a first power is estimated, which is the maximum power consumption in one year when the target device is operated with demand control applied, and a second power is estimated, which is the maximum power consumption in one year when the target device is operated without demand control applied, and air conditioning control information is generated that includes a result of comparing the first power and the second power.

[0172] This makes it possible to show information comparing power consumption over a one-year period as the effect of reducing power consumption when demand control is applied.

[0173] The information output system 1000 outputs information about an air conditioning system 1 in a building BL. The information output system 1000 includes a period estimation unit 202, an identification unit 203, an information generation unit 204, and an output unit 205. The period estimation unit 202 estimates the peak period during which the power consumption per unit period of the air conditioning system 1 or the power consumption per unit period of all the equipment in the building BL, including the air conditioning system 1, is at its highest. When the building BL is divided into multiple areas AL, the identification unit 203 identifies an area AL that has a higher heat load during the peak period than other areas AL. The identification unit 203 identifies, as a target device, the air conditioner 11 that performs air conditioning in the identified area AL among the air conditioners 11 included in the air conditioning system 1. The information generation unit 204 generates air conditioning control information that recommends demand control that limits the output of the target device during the peak period. The output unit 205 outputs the air conditioning control information. This provides the same effects as the information output method described above.

[0174] The program 221 causes the processor 200, which outputs information about the air conditioning equipment 1 of the building BL, to function as a period estimation unit 202, an identification unit 203, an information generation unit 204, and an output unit 205. The period estimation unit 202 estimates the peak period during which the power consumption per unit period of the air conditioning equipment 1 or the power consumption per unit period of all the equipment in the building BL, including the air conditioning equipment 1, is at its highest. The identification unit 203 identifies, among the areas AL in the case where the building BL is divided into multiple areas AL, an area AL whose heat load during the peak period is greater than that of the other areas AL. The identification unit 203 identifies, as the target device, the air conditioner 11 that performs air conditioning in the identified area AL among the air conditioners 11 included in the air conditioning equipment 1. The information generation unit 204 generates air conditioning control information that recommends demand control that limits the output of the target device during the peak period. The output unit 205 outputs the air conditioning control information. This provides the same effects as the information output method described above.

[0175] The information output method executed by the information output system 1000 of this embodiment is an information output method that outputs information related to the air conditioning equipment 1 of a building BL using a computer. The method includes an acquisition step of acquiring usage information including the usage start time of the building BL. The method also includes a heat load calculation step of calculating the heat load at the usage start time for each area AL when the building BL is divided into multiple areas AL. The method also includes an area identification step of identifying an area AL whose heat load per unit area at the usage start time is greater than that of other areas AL, and an apparatus identification step of identifying, as a target apparatus, an air conditioner 11 that will condition the identified area AL, among the air conditioners 11 included in the air conditioning equipment 1. The method also includes an information generation step of generating air conditioning control information that recommends that the target apparatus perform either pre-cooling operation, which starts cooling operation before the usage start time, or pre-heating operation, which starts heating operation before the usage start time. The method also includes an output step of outputting the air conditioning control information.

[0176] This makes it possible to effectively reduce power consumption by the air conditioning equipment 1 during peak hours by recommending control to operate the air conditioner 11 before use begins for areas AL in the building BL where the heat load is high at the start of use. Therefore, it is possible to reduce power consumption by the air conditioning equipment 1 and the energy consumption of the building BL.

[0177] In the information generating step, the information output method generates a prediction model 216 that calculates the time required for pre-cooling operation or pre-heating operation from a plurality of data including at least the start time of pre-cooling operation or pre-heating operation, the start time of use, and the indoor temperature of area AL at the start time of pre-cooling operation or pre-heating operation. Then, by providing the start time of use of area AL and the set temperature to prediction model 216, the time required for pre-cooling operation or pre-heating operation is estimated.

[0178] According to this, it is possible to easily find the time required for pre-cooling operation or pre-heating operation using the prediction model 216. Furthermore, the prediction model 216 can be generated by regression analysis or AI machine learning using the simulation results of the simulation model 211, and by such a method, it is possible to obtain a highly accurate prediction model 216 without running a simulator. The plurality of data may also include the time difference between the start time of the pre-cooling operation or pre-heating operation and the start time of use, and the difference between the indoor temperature of area AL at the start time of the pre-cooling operation or pre-heating operation and the indoor temperature of area AL at the start time of use. Furthermore, the prediction model 216 may be provided with the indoor temperature of area AL and the set temperature at the start time of use to estimate the time required for the pre-cooling operation or pre-heating operation.

[0179] The information output method includes an operation time determination step for determining a start time for pre-cooling operation or pre-heating operation. Then, in an area identification step, multiple areas AL are identified, including an area AL whose heat load per unit area at the start time of use is greater than that of other areas AL. Then, in an apparatus identification step, multiple air conditioners 11 included in the air conditioning equipment 1 that will condition the identified multiple areas AL are identified as target apparatuses. Then, in an operation time determination step, the indoor temperature of the area AL at the start time of use when the target apparatuses are to be operated from multiple different operation start times is calculated. Then, the start time for pre-cooling operation or pre-heating operation is determined based on the difference between the calculated indoor temperature of the area AL and the set temperature at the start time of use. Then, in an information generation step, if the difference between the start times of pre-cooling operation or pre-heating operation determined for the multiple target apparatuses is equal to or less than a predetermined value, air conditioning control information is generated that recommends adjusting the start times of pre-cooling operation or pre-heating operation.

[0180] This allows the start time of pre-cooling operation or pre-heating operation to be determined so that the indoor temperature in area AL, which has a high heat load, is kept at an appropriate temperature. Therefore, the peak power consumption of the air conditioning equipment can be reduced by pre-cooling operation or pre-heating operation without compromising the comfort of area AL, which is the space to be conditioned. Note that the operating data of the air conditioner model, such as the start time of pre-cooling operation or pre-heating operation determined using this method, may be used to create the aforementioned prediction model 216.

[0181] The information output system 1000 outputs information about the air conditioning equipment 1 of a building BL. The information output system 1000 includes an acquisition unit 201, an identification unit 203, an information generation unit 204, and an output unit 205. The acquisition unit 201 acquires usage information including the use start time of the building BL. When the building BL is divided into multiple areas AL, the identification unit 203 calculates the heat load at the use start time for each area AL. The identification unit 203 identifies an area AL whose heat load per unit area at the use start time is greater than that of other areas AL. The identification unit 203 identifies, as a target device, an air conditioner 11 that conditions the identified area AL among the air conditioners 11 included in the air conditioning equipment 1. The information generation unit 204 generates air conditioning control information that recommends that the target device perform either pre-cooling operation, which starts cooling operation before the use start time, or pre-heating operation, which starts heating operation before the use start time. The output unit 205 outputs the air conditioning control information.

[0182] This provides the same effects as the information output method described above.

[0183] The program 221 causes the processor 200, which outputs information about the air conditioning equipment 1 of the building BL, to function as an acquisition unit 201, an identification unit 203, an information generation unit 204, and an output unit 205. The acquisition unit 201 acquires usage information including the use start time of the building BL. When the building BL is divided into multiple areas AL, the identification unit 203 calculates the heat load at the use start time for each area AL. The identification unit 203 identifies an area AL whose heat load per unit area at the use start time is greater than that of other areas AL. The identification unit 203 identifies, as a target device, an air conditioner 11 that conditions the identified area AL among the air conditioners 11 included in the air conditioning equipment 1. The information generation unit 204 generates air conditioning control information that recommends that the target device perform either pre-cooling operation, which starts cooling operation before the use start time, or pre-heating operation, which starts heating operation before the use start time. The output unit 205 outputs the air conditioning control information.

[0184] This provides the same effects as the information output method described above.

[0185] The information output method executed by the information output system 1000 of this embodiment is an information output method that outputs information related to the air conditioning equipment 1 of a building BL by a computer. It includes an acquisition step of acquiring usage information including the usage end time of the building BL. It also includes an area identification step of identifying, when the building BL is divided into multiple areas AL, an area AL whose heat load per unit area at the usage end time satisfies a predetermined condition among each area AL. It also includes an apparatus identification step of identifying, as a target apparatus, an air conditioner 11 that conditions the identified area AL among the air conditioners 11 included in the air conditioning equipment 1. It also includes an information generation step of generating air conditioning control information that recommends early shutdown control for the target apparatus, which stops operation before the usage end time. It also includes an output step of outputting the air conditioning control information.

[0186] According to this, it is recommended that early stop control, which stops the air conditioner 11 before the end of use of the building BL, be performed on the area AL that is suitable for early stop control, so that the power consumption of the air conditioning equipment 1 can be effectively reduced without compromising the comfort of the conditioned space. Therefore, it is possible to achieve a reduction in the power consumption of the air conditioning equipment 1 and a reduction in the energy consumption of the building BL.

[0187] In the information output method, the area specifying step specifies one or more areas AL among a plurality of areas AL of the building BL, the area AL having a heat load per unit area during cooling that is relatively smaller than the other areas AL.

[0188] This identifies an area AL that is suitable for early shutdown control during cooling operation, thereby effectively reducing the power consumption of the air conditioning equipment 1 without compromising the comfort of the conditioned space. Also, in the area identification step, for example, an area AL where the heat load per unit area during cooling is minimum may be identified.

[0189] In the information output method, the area specifying step specifies one or more areas AL among a plurality of areas AL of the building BL, the area AL having a heat load per unit area during heating that is relatively larger than the other areas AL.

[0190] According to this, an area AL suitable for early stop control during heating operation is identified, so that the power consumption of the air conditioning equipment 1 can be effectively reduced without impairing the comfort of the space to be conditioned.

[0191] The information output system 1000 outputs information about the air conditioning equipment 1 of the building BL. The information output system 1000 includes an acquisition unit 201, an identification unit 203, an information generation unit 204, and an output unit 205. The acquisition unit 201 acquires usage information including the usage end time of the building BL. When the building BL is divided into multiple areas AL, the identification unit 203 identifies an area AL whose heat load per unit area at the usage end time satisfies a predetermined condition. The identification unit 203 identifies, as a target device, an air conditioner 11 that conditions the identified area AL among the air conditioners 11 included in the air conditioning equipment 1. The information generation unit 204 generates air conditioning control information that recommends early shutdown control for the target device, which stops operation before the usage end time. The output unit 205 outputs the air conditioning control information.

[0192] This provides the same effects as the information output method described above.

[0193] The program 221 causes the processor 200, which outputs information about the air conditioning equipment 1 of the building BL, to function as an acquisition unit 201, an identification unit 203, an information generation unit 204, and an output unit 205. The acquisition unit 201 acquires usage information including the usage end time of the building BL. When the building BL is divided into multiple areas AL, the identification unit 203 identifies, from each area AL, an area AL whose heat load per unit area at the usage end time satisfies a predetermined condition. The identification unit 203 identifies, as the target device, the air conditioner 11 that conditions the identified area AL from among the air conditioners 11 included in the air conditioning equipment 1. The information generation unit 204 generates air conditioning control information that recommends early shutdown control for the target device, which stops operation before the usage end time. The output unit 205 outputs the air conditioning control information.

[0194] This provides the same effects as the information output method described above.

[0195] (Other embodiments) As described above, the above-mentioned first embodiment has been described as an example disclosed in the present application. However, the technology in the present disclosure is not limited to this, and can be applied to embodiments in which modifications, substitutions, additions, omissions, etc. are made. Furthermore, it is also possible to combine the components described in the above-mentioned first embodiment to create new embodiments. Therefore, other embodiments will be exemplified below.

[0196] In the above embodiment, an example has been described in which the terminal device 2 generates the recommendation data 224 and the operational data 225 and outputs them to the server device 3 or another device. This is just one example, and for example, by implementing the functions of the terminal device 2 in the server device 3 or another device, a configuration can be realized in which the device executes the various functions shown in Figures 4 to 9. In this case, the functions of the terminal device 2 are realized, for example, as an application program executable by a computer other than the terminal device 2.

[0197] The processor 200 may be configured with a single processor or multiple processors. The processor 200 may be hardware programmed to implement corresponding functional units. That is, these processors may be configured with, for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0198] The configuration of the terminal device 2 shown in Figure 1 is an example, and the specific implementation form is not particularly limited. In other words, it is not necessarily necessary to implement hardware corresponding to each unit individually, and it is also possible to configure the functions of each unit to be realized by a single processor executing a program. Furthermore, some of the functions realized by software in the above-mentioned embodiment may be realized by hardware, or some of the functions realized by hardware may be realized by software.

[0199] The step units of the operations shown in Figures 4, 5, 6, 8, and 9 are divided according to the main processing content to make the operations easier to understand, and the operation is not limited by the way the processing units are divided or the names of the processing units. The operations may be divided into more step units depending on the processing content. Furthermore, one step unit may be divided so that it includes more processing. Furthermore, the order of the steps may be changed as appropriate within the scope that does not interfere with the purpose of this disclosure.

[0200] It should be noted that the above-described embodiments are intended to illustrate the technology of the present disclosure, and various modifications, substitutions, additions, omissions, etc. may be made within the scope of the claims or their equivalents.

[0201] (Addendum) The above description of the embodiments discloses the following techniques.

[0202] (Technology 1) An information output method for outputting information related to the air conditioning equipment of a building by a computer, the information output method including: a period estimation step for estimating a peak period during a planning period when the power consumption per unit period of the air conditioning equipment or the power consumption per unit period of all the equipment in the building including the air conditioning equipment will be the highest; an area identification step for identifying, when the building is divided into multiple areas, an area whose heat load during the peak period is greater than that of the other areas; an information generation step for identifying, as a target device, the air conditioning device that performs air conditioning in the identified area among the air conditioning devices included in the air conditioning equipment, and generating air conditioning control information that recommends demand control to limit the output of the target device during the peak period; and an output step for outputting the air conditioning control information. This allows for effective reduction of power consumption by the building's air conditioning equipment by recommending demand control in areas of the building with high heat loads, thereby achieving reduction of power consumption by the air conditioning equipment and a reduction in the building's energy consumption.

[0203] (Technology 2) The information output method described in Technology 1 includes a heat load calculation step of determining the heat load during the peak period estimated in the period estimation step for each of the areas of the building, and in the area identification step, an area of ​​the multiple areas of the building is identified that has a higher heat load during the peak period than the other areas. According to this, by calculating the heat load of an area, it is possible to appropriately identify an area where the effect of demand control is large.

[0204] (Technology 3) The information output method according to Technology 1 or Technology 2, wherein in the period estimation step, the estimated reference date is either the hottest day or the coldest day of the year in the area where the building is installed, or the next usage day after consecutive non-usage days in the building usage schedule, and the peak period is estimated so as to overlap with the day on which the power consumption of the air conditioning equipment is at its maximum within a predetermined range from the estimated reference date. This allows areas with high thermal loads to be identified on days when the power consumption of the air conditioning equipment is high, making it possible to identify areas where demand control can be highly effective and efficiently identify areas with high thermal loads.

[0205] (Technology 4) An information output method according to any one of Technology 1 to Technology 3, wherein in the information generation step, the power consumption of the target device during the peak period is predicted, and information regarding demand control of the target device is generated based on a ratio between an integrated value of the predicted power consumption and a rated power consumption of the target device. This allows the set values ​​for demand control to be determined appropriately, thereby achieving more effective demand control.

[0206] (Technology 5) An information output method according to any one of Technology 1 to Technology 4, wherein in the information generation step, a calculation model is generated that estimates an integrated value of the power consumption of the target device from the outside air temperature based on at least data on the annual power consumption of the target device and data on the annual outside air temperature, and information related to the demand control is generated by providing a predicted value of the outside air temperature to the calculation model. According to this, by using the calculation model, the power consumption of the target device can be easily calculated from the forecast value of the outside air temperature obtained from the weather forecast or the like.

[0207] (Technology 6) The information output method according to any one of Technology 1 to Technology 5, wherein in the information generation step, a first operating mode in which the target device is operated by applying demand control and a second operating mode in which the target device is operated without applying demand control are set, the indoor temperature on at least one of the hottest day and the coldest day of the year in the area where the building is installed is estimated for each of the first operating mode and the second operating mode, and the air conditioning control information is generated including information comparing the indoor temperatures estimated for each of the first operating mode and the second operating mode. This makes it possible to output information comparing the power consumption of the first air conditioner and the second air conditioner, along with the presence or absence of demand control.

[0208] (Technology 7) An information output method according to any one of Technology 1 to Technology 6, wherein in the information generation step, a first power is estimated, which is the maximum power consumption in one year when the target device is operated with demand control applied, and a second power is estimated, which is the maximum power consumption in one year when the target device is operated without demand control applied, and the air conditioning control information is generated including a result of comparing the first power and the second power. This makes it possible to output the power consumption reduction effect when demand control is applied as information comparing power consumption over a one-year period.

[0209] (Technology 8) An information output method for outputting information about the air conditioning equipment of a building by a computer, the information output method including: an acquisition step for acquiring usage information including the start time of use of the building; a heat load calculation step for calculating the heat load at the start time of use for each of the areas when the building is divided into a plurality of areas; an area identification step for identifying an area having a higher heat load per unit area at the start time of use than other areas; an apparatus identification step for identifying, as a target apparatus, an air conditioning apparatus included in the air conditioning equipment that will air condition the identified area; an information generation step for generating air conditioning control information that recommends that the target apparatus perform either a pre-cooling operation that starts cooling operation before the start time of use, or a pre-heating operation that starts heating operation before the start time of use; and an output step for outputting the air conditioning control information. This allows for effective reduction of power consumption by air conditioning equipment during peak hours by recommending control to operate air conditioning units before use begins in areas of the building where the heat load is high at the start of use. This makes it possible to reduce power consumption by air conditioning equipment and the energy consumption of the building.

[0210] (Technology 9) In the information generation step, a calculation model is generated that calculates the time required for the pre-cooling operation or the pre-heating operation from a plurality of data including at least the start time of the pre-cooling operation or the pre-heating operation, the start time of use, and the indoor temperature of the area at the start time of the pre-cooling operation or the pre-heating operation, and the time required for the pre-cooling operation or the pre-heating operation is estimated by providing the start time of use and the set temperature of the area to the calculation model. This makes it possible to easily determine the time required for the pre-cooling operation or the pre-heating operation by using a calculation model.

[0211] (Technology 10) An information output method according to Technology 8, comprising an operation time determination step for determining a start time of the pre-cooling operation or the pre-heating operation, wherein the area identification step identifies a plurality of areas including the area having a larger heat load per unit area at the usage start time than the other areas, the device identification step identifies a plurality of air conditioning devices included in the air conditioning equipment that will condition the identified plurality of areas as target devices, the operation time determination step calculates indoor temperatures in the areas at the usage start time when the target devices are operated from a plurality of different operation start times, and determines the start time of the pre-cooling operation or the pre-heating operation based on the difference between the calculated indoor temperatures in the areas and the set temperature at the usage start time, and the information generation step generates the air conditioning control information recommending adjustment of the start time of the pre-cooling operation or the pre-heating operation when the difference between the start times of the pre-cooling operation or the pre-heating operation determined for the plurality of target devices is equal to or less than a predetermined value. This allows the start time of pre-cooling or pre-heating operation to be determined so that the indoor temperature in areas with high air conditioning loads is at an appropriate temperature. Therefore, the power consumption of the air conditioning equipment can be reduced by pre-cooling or pre-heating operation without compromising the comfort of the conditioned space.

[0212] (Technology 11) An information output method for outputting information about the air conditioning equipment of a building by a computer, the information output method including: an acquisition step for acquiring usage information including the end time of use of the building; an area identification step for identifying, when the building is divided into multiple areas, an area in which the heat load per unit area at the end time of use satisfies a predetermined condition; an apparatus identification step for identifying, as a target apparatus, an air conditioning apparatus included in the air conditioning equipment that performs air conditioning in the identified area; an information generation step for generating air conditioning control information that recommends early stop control for the target apparatus to stop operation before the end time of use; and an output step for outputting the air conditioning control information. This system recommends that early shutdown control, which shuts down air conditioners before the end of building use, be performed in areas suitable for early shutdown control, thereby effectively reducing the power consumption of air conditioning equipment without compromising the comfort of the conditioned space. This makes it possible to reduce the power consumption of air conditioning equipment and reduce the energy consumption of the building.

[0213] (Technology 12) The information output method described in Technology 11, wherein the area identification step identifies one or more areas among the multiple areas of the building that have a relatively smaller heat load per unit area during cooling than the other areas. This allows for identifying areas suitable for early shutdown control during cooling operation, thereby effectively reducing power consumption by the air conditioning equipment without compromising the comfort of the space to be conditioned.

[0214] (Technology 13) The information output method according to Technology 11 or Technology 12, wherein in the area identification step, one or more areas of the plurality of areas of the building are identified that have a relatively larger heat load per unit area during heating than the other areas. This allows for identifying areas suitable for early shutdown control during heating operation, thereby effectively reducing power consumption by the air conditioning equipment without compromising the comfort of the space to be conditioned.

[0215] (Technology 14) An information output system that outputs information related to the air conditioning equipment of a building, comprising: a period estimation unit that estimates a peak period during which the power consumption per unit period of the air conditioning equipment, or the power consumption per unit period of all the equipment in the building including the air conditioning equipment, is at its highest in an year; an area identification unit that identifies, when the building is divided into multiple areas, an area that has a higher heat load during the peak period than the other areas; an information generation unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the area identified by the area identification unit as a target device, and generates air conditioning control information that recommends demand control to limit the output of the target device during the peak period; and an output unit that outputs the air conditioning control information. This allows for effective reduction of power consumption by the building's air conditioning equipment by recommending demand control in areas of the building with high heat loads, thereby achieving reduction of power consumption by the air conditioning equipment and a reduction in the building's energy consumption.

[0216] (Technology 15) An information output system that outputs information related to the air conditioning equipment of a building, comprising: an acquisition unit that acquires usage information including the start time of use of the building; a heat load calculation unit that calculates the heat load at the start time of use for each of the areas when the building is divided into multiple areas; an area identification unit that identifies an area with a higher heat load per unit area at the start time of use than the other areas; an apparatus identification unit that identifies, from among the air conditioning devices included in the air conditioning equipment, the air conditioning device that will perform the air conditioning of the identified area as a target device; an information generation unit that generates air conditioning control information that recommends that the target device perform either pre-cooling operation, which starts cooling operation before the start time of use, or pre-heating operation, which starts heating operation before the start time of use; and an output unit that outputs the air conditioning control information. This allows for effective reduction of power consumption by air conditioning equipment during peak hours by recommending control to operate air conditioning units before use begins in areas of the building where the heat load is high at the start of use. This makes it possible to reduce power consumption by air conditioning equipment and the energy consumption of the building.

[0217] (Technology 16) An information output system that outputs information related to the air conditioning equipment of a building, comprising: an acquisition unit that acquires usage information including the end time of use of the building; an area identification unit that identifies, when the building is divided into multiple areas, an area in which the heat load per unit area at the end time of use satisfies predetermined conditions; an apparatus identification unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the identified area as a target device; an information generation unit that generates air conditioning control information that recommends early stop control for the target device to stop operation before the end time of use; and an output unit that outputs the air conditioning control information. This system recommends that early shutdown control, which shuts down air conditioners before the end of building use, be performed in areas suitable for early shutdown control, thereby effectively reducing the power consumption of air conditioning equipment without compromising the comfort of the conditioned space. This makes it possible to reduce the power consumption of air conditioning equipment and reduce the energy consumption of the building.

[0218] (Technology 17) A program that causes a processor that outputs information about the air conditioning equipment of a building to function as: a period estimation unit that estimates the peak period during which the power consumption per unit period of the air conditioning equipment, or the power consumption per unit period of all the equipment in the building including the air conditioning equipment, is the largest in an year; an area identification unit that identifies, when the building is divided into multiple areas, an area that has a higher heat load during the peak period than the other areas; an information generation unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the area identified by the area identification unit as a target device, and generates air conditioning control information that recommends demand control to limit the output of the target device during the peak period; and an output unit that outputs the air conditioning control information. This allows for effective reduction of power consumption by the building's air conditioning equipment by recommending demand control in areas of the building with high heat loads, thereby achieving reduction of power consumption by the air conditioning equipment and a reduction in the building's energy consumption.

[0219] (Technology 18) A program that causes a processor that outputs information about the air conditioning equipment of a building to function as an acquisition unit that acquires usage information including the start time of use of the building, a heat load calculation unit that calculates the heat load at the start time of use for each of the areas when the building is divided into multiple areas, an area identification unit that identifies an area with a higher heat load per unit area at the start time of use than the other areas, an apparatus identification unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that will perform air conditioning in the identified area as a target device, an information generation unit that generates air conditioning control information that recommends that the target device perform either pre-cooling operation, which starts cooling operation before the start time of use, or pre-heating operation, which starts heating operation before the start time of use, and an output unit that outputs the air conditioning control information. This allows for effective reduction of power consumption by air conditioning equipment during peak hours by recommending control to operate air conditioning units before use begins in areas of the building where the heat load is high at the start of use. This makes it possible to reduce power consumption by air conditioning equipment and the energy consumption of the building.

[0220] (Technology 19) A program that causes a processor that outputs information about a building's air conditioning equipment to function as an acquisition unit that acquires usage information including the end time of use of the building, an area identification unit that identifies, when the building is divided into multiple areas, an area in which the heat load per unit area at the end time of use satisfies specified conditions, an apparatus identification unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that conditions the identified area as a target device, an information generation unit that generates air conditioning control information that recommends early stop control for the target device to stop operation before the end time of use, and an output unit that outputs the air conditioning control information. This system recommends that early shutdown control, which shuts down air conditioners before the end of building use, be performed in areas suitable for early shutdown control, thereby effectively reducing the power consumption of air conditioning equipment without compromising the comfort of the conditioned space. This makes it possible to reduce the power consumption of air conditioning equipment and reduce the energy consumption of the building. [Industrial Applicability]

[0221] As described above, the information output method, information output system, and program according to the present invention enable a reduction in the energy consumption of a building by suppressing the power consumption of air conditioning equipment, and can be used to improve the operation of existing air conditioning equipment and to introduce appropriate new air conditioning equipment. [Explanation of symbols]

[0222] 1. Air conditioning equipment 2. Terminal Device 3. Server equipment 10 Air conditioning control device 11, 11A, 11B, 11C, 11D Air conditioner (air conditioning device) 12 Outdoor unit 13 Indoor unit 14 Refrigerant circuit 20 Control device 25 Communications Department 31 Information display screen 32 Recommended Messages 33 Content Description Display 34 Comparative Data 35 Comparative Data 41 DB 42 Building Data 43 Area Data 44 Weather Data 45 Air Conditioning Equipment Data 47 Planning Data 48 Existing Building Data 200 processors 201 Acquisition Department 202 Period Estimation Department 203 Specific section 204 Information generation section 205 Output section 220 memory 221 Program 224 Recommended Data (Air Conditioning Control Information) 225 Operational data (air conditioning control information) 1000 Information Output System AL Area BL Building NW Network

Claims

1. An information output method for outputting information about an air conditioning system of a building by a computer, comprising: a period estimation step of estimating a peak period during which the power consumption per unit period of the air conditioning equipment or the power consumption per unit period of all the equipment devices in the building including the air conditioning equipment is at its maximum in an year; an area identification step of identifying an area in which the heat load during the peak period is greater than the other areas when the building is divided into a plurality of areas; an information generation step of identifying, as a target device, the air conditioning device that performs air conditioning in the area identified in the area identification step, among the air conditioning devices included in the air conditioning equipment, and generating air conditioning control information that recommends demand control to limit the output of the target device during the peak period; and an output step of outputting the air conditioning control information. Information output method.

2. a heat load calculation step of calculating a heat load during the peak period estimated in the period estimation step for each of the areas of the building; The information output method according to claim 1 , wherein the area specifying step specifies an area among the plurality of areas of the building in which the heat load during the peak period is greater than the other areas.

3. In the period estimation step, The estimated reference date is either the hottest day or the coldest day of the year in the area where the building is installed, or the next day of use after consecutive days of non-use in the building's usage schedule, The information output method according to claim 1 , wherein the peak period is estimated so as to coincide with a day on which power consumption of the air conditioning equipment is at its maximum within a predetermined range from the estimated reference date.

4. 2. The information output method according to claim 1, wherein the information generation step predicts the power consumption of the target device during the peak period, and generates information regarding demand control of the target device based on a ratio between an integrated value of the predicted power consumption and a rated power consumption of the target device.

5. In the information generating step, a calculation model is generated based on at least annual data on the power consumption of the target device and annual data on outdoor air temperature, for estimating an integrated value of the power consumption of the target device from the outdoor air temperature; The information output method according to claim 1 , wherein the information relating to the demand control is generated by providing a predicted value of an outside air temperature to the calculation model.

6. In the information generating step, A first operating mode in which the target device is operated by applying demand control and a second operating mode in which the target device is operated without applying demand control are set; estimating the indoor temperature on at least one of the hottest day and the coldest day of the year in an area where the building is installed in each of the first operating mode and the second operating mode; The information output method according to claim 1 , further comprising generating the air-conditioning control information including information comparing the indoor temperatures estimated in the first operating mode and the second operating mode.

7. In the information generating step, estimating a first power, which is a maximum power consumption in one year when the target device is operated by applying demand control; A second power is estimated, which is a maximum power consumption in one year when the target device is operated without applying demand control; The information output method according to claim 1 , further comprising generating the air conditioning control information including a result of comparing the first power with the second power.

8. An information output method for outputting information about an air conditioning system of a building by a computer, comprising: an acquisition step of acquiring usage information including a start time of use of the building; a heat load calculation step of calculating a heat load at the use start time for each of the areas when the building is divided into a plurality of areas; an area specifying step of specifying an area in which the heat load per unit area at the use start time is larger than other areas; an apparatus identification step of identifying, as a target apparatus, the air conditioning apparatus that performs air conditioning in the identified area, from among the air conditioning apparatuses included in the air conditioning equipment; an information generating step of generating air conditioning control information that recommends that the target device perform either a pre-cooling operation in which a cooling operation is started before the use start time or a pre-heating operation in which a heating operation is started before the use start time; and an output step of outputting the air conditioning control information. Information output method.

9. In the information generating step, generating a calculation model for calculating the time required for the pre-cooling operation or the pre-heating operation from a plurality of data including at least the start time of the pre-cooling operation or the pre-heating operation, the start time of use, and the indoor temperature of the area at the start time of the pre-cooling operation or the pre-heating operation; The information output method according to claim 8 , wherein the time required for the pre-cooling operation or the pre-heating operation is estimated by providing the use start time and the set temperature of the area to the calculation model.

10. an operation time determination step of determining a start time of the pre-cooling operation or the pre-heating operation, In the area specifying step, a plurality of areas including the area having a larger heat load per unit area at the use start time than other areas are specified; In the device identification step, a plurality of air conditioning devices that perform air conditioning in the identified plurality of areas are identified as target devices from among the air conditioning devices included in the air conditioning equipment; In the operation time determination step, calculating an indoor temperature in the area at a start time of use when the target device is operated from a plurality of different start times of operation; determining a start time of the pre-cooling operation or the pre-heating operation based on a difference between the determined indoor temperature of the area and a set temperature at the use start time; In the information generating step, 9. The information output method according to claim 8, wherein when a difference between the start times of the pre-cooling operation or the pre-heating operation determined for a plurality of the target devices is equal to or less than a predetermined value, the air conditioning control information is generated to recommend adjusting the start times of the pre-cooling operation or the pre-heating operation.

11. An information output method for outputting information about an air conditioning system of a building by a computer, comprising: an acquisition step of acquiring usage information including a usage end time of the building; an area identification step of identifying an area in which a heat load per unit area at the end time of use satisfies a predetermined condition among each of the areas when the building is divided into a plurality of areas; an apparatus identification step of identifying, as a target apparatus, the air conditioning apparatus that performs air conditioning in the identified area, from among the air conditioning apparatuses included in the air conditioning equipment; an information generating step of generating air conditioning control information that recommends early stop control for stopping operation of the target device before the end time of use; and an output step of outputting the air conditioning control information. Information output method.

12. The information output method according to claim 11 , wherein the area specifying step specifies one or more areas among the plurality of areas of the building in which a heat load per unit area during cooling is relatively smaller than that of the other areas.

13. The information output method according to claim 11 , wherein the area specifying step specifies one or more areas among the plurality of areas of the building that have a relatively larger heat load per unit area during heating than the other areas.

14. An information output system that outputs information about an air conditioning system of a building, a period estimation unit that estimates a peak period during which the power consumption per unit period of the air conditioning equipment or the power consumption per unit period of all facility equipment in the building including the air conditioning equipment is at its maximum in an year; an area specifying unit that specifies, among the areas when the building is divided into a plurality of areas, an area in which the heat load during the peak period is larger than the other areas; an information generating unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the area identified by the area identifying unit as a target device, and generates air conditioning control information that recommends demand control that limits the output of the target device during the peak period; an output unit that outputs the air conditioning control information, Information output system.

15. An information output system that outputs information about an air conditioning system of a building, an acquisition unit that acquires usage information including a usage start time of the building; a load calculation unit that calculates a heat load at the use start time for each of a plurality of areas when the building is divided into the plurality of areas; an area specifying unit that specifies the area in which the heat load per unit area at the use start time is larger than the other areas; an apparatus identification unit that identifies, as a target apparatus, the air conditioning apparatus that performs air conditioning in the identified area, from among the air conditioning apparatuses included in the air conditioning equipment; an information generation unit that generates air conditioning control information that recommends that the target device perform either a pre-cooling operation in which a cooling operation is started before the use start time or a pre-heating operation in which a heating operation is started before the use start time; and an output unit that outputs the air conditioning control information, Information output system.

16. An information output system that outputs information about an air conditioning system of a building, an acquisition unit that acquires usage information including a usage end time of the building; an area specifying unit that specifies, among the areas when the building is divided into a plurality of areas, an area in which a heat load per unit area at the end time of use satisfies a predetermined condition; an apparatus identification unit that identifies, as a target apparatus, the air conditioning apparatus that performs air conditioning in the identified area, from among the air conditioning apparatuses included in the air conditioning equipment; an information generating unit that generates air conditioning control information that recommends early stop control for stopping operation of the target device before the end time of use; an output unit that outputs the air conditioning control information, Information output system.

17. a processor that outputs information about the air conditioning equipment of a building; a period estimation unit that estimates a peak period during which the power consumption per unit period of the air conditioning equipment or the power consumption per unit period of all facility equipment in the building including the air conditioning equipment is at its maximum in an year; an area specifying unit that specifies, among the areas when the building is divided into a plurality of areas, an area in which the heat load during the peak period is larger than the other areas; an information generating unit that identifies, among the air conditioning devices included in the air conditioning equipment, the air conditioning device that performs air conditioning in the area identified by the area identifying unit as a target device, and generates air conditioning control information that recommends demand control that limits the output of the target device during the peak period; The output unit functions as an output unit that outputs the air conditioning control information. program.

18. a processor that outputs information about the air conditioning equipment of a building; an acquisition unit that acquires usage information including a usage start time of the building; a load calculation unit that calculates a heat load at the use start time for each of a plurality of areas when the building is divided into the plurality of areas; an area specifying unit that specifies the area in which the heat load per unit area at the use start time is larger than the other areas; an apparatus identification unit that identifies, as a target apparatus, the air conditioning apparatus that performs air conditioning in the identified area, from among the air conditioning apparatuses included in the air conditioning equipment; an information generation unit that generates air conditioning control information that recommends that the target device perform either a pre-cooling operation in which a cooling operation is started before the use start time or a pre-heating operation in which a heating operation is started before the use start time; and The output unit functions as an output unit that outputs the air conditioning control information. program.

19. a processor that outputs information about the air conditioning equipment of a building; an acquisition unit that acquires usage information including a usage end time of the building; an area specifying unit that specifies, among the areas when the building is divided into a plurality of areas, an area in which a heat load per unit area at the end time of use satisfies a predetermined condition; an apparatus identification unit that identifies, as a target apparatus, the air conditioning apparatus that performs air conditioning in the identified area, from among the air conditioning apparatuses included in the air conditioning equipment; an information generating unit that generates air conditioning control information that recommends early stop control for stopping operation of the target device before the end time of use; The output unit functions as an output unit that outputs the air conditioning control information. program.

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