Facility management system, facility management method, and facility management program

Abstract

To provide a facility management system capable of optimizing an energy consumption of a facility using various data on the facility, a facility management method, and a facility management program.SOLUTION: A facility management system comprises: an acquisition processing unit which acquires facility data including measurement data of equipment in a facility and environment data corresponding to the facility; an identification processing unit which identifies whether each of the facility data acquired by the acquisition processing unit can adjust or cannot adjust an output value by a setting operation of the equipment; and an estimation processing unit which estimates an optimum setting value of first facility data on the basis of the adjustable first facility data corresponding to first equipment and unadjustable second facility data related to the first facility data.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a facility management system, a facility management method, and a facility management program for managing the energy consumption of a facility.

Background Art

[0002] Conventionally, a system for managing the energy consumption of a facility has been known. For example, there is known a system that estimates the set values of equipment installed in a facility such as a building based on various data and optimizes the energy consumption (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, in a facility, it is possible to manage equipment using a communication standard for constructing a building network such as BACnet (Building Automation and Control Networking Protocol) (「BACnet」; registered trademark). The data obtained using BACnet includes not only the measurement data of the equipment but also the detection data (such as environmental data) of various sensors installed in the facility. With the conventional technology, it is difficult to optimize the energy consumption of the equipment in the facility by using various data related to the facility.

[0005] An object of the present invention is to provide a facility management system, a facility management method, and a facility management program capable of optimizing the energy consumption of a facility by using various data related to the facility.

Means for Solving the Problems

[0006] A facility management system according to one aspect of the present invention includes: an acquisition processing unit that acquires facility data including measurement data of equipment within a facility and environmental data corresponding to the facility; an identification processing unit that identifies whether each of the facility data acquired by the acquisition processing unit is data with an adjustable output value or data with an inadjustable output value; and an estimation processing unit that estimates the optimal setting value of the first facility data based on adjustable first facility data corresponding to a first piece of equipment and inadjustable second facility data related to the first facility data.

[0007] Another aspect of the present invention relates to a facility management method which includes: an acquisition step in which one or more processors acquire facility data including measurement data of equipment within the facility and environmental data corresponding to the facility; an identification step in which each of the facility data acquired in the acquisition step is identified as either data with an adjustable output value or data with an inflexible output value; and an estimation step in which the optimal setting value of the first facility data is estimated based on adjustable first facility data corresponding to the first equipment and inflexible second facility data related to the first facility data.

[0008] A facility management program according to another aspect of the present invention is a facility management program that causes one or more processors to execute: an acquisition step of acquiring facility data including measurement data of equipment within a facility and environmental data corresponding to the facility; an identification step of each of the facility data acquired in the acquisition step, identifying whether the output value is adjustable or not; and an estimation step of estimating the optimal setting value of the first facility data based on adjustable first facility data corresponding to the first equipment and non-adjustable second facility data related to the first facility data. [Effects of the Invention]

[0009] According to the present invention, it is possible to provide a facility management system, a facility management method, and a facility management program that can optimize the energy consumption of a facility by utilizing various data related to the facility. [Brief explanation of the drawing]

[0010] [Figure 1] Figure 1 is a block diagram showing the configuration of a facility management system according to an embodiment of the present invention. [Figure 2] Figure 2 shows an example of a monitoring equipment information database used in a facility management system according to an embodiment of the present invention. [Figure 3] Figure 3 shows an example of a facility data information database used in a facility management system according to an embodiment of the present invention. [Figure 4] Figure 4 shows an example of data names included in the facility data information DB according to an embodiment of the present invention. [Figure 5] Figure 5 shows an example of an adjustment feasibility information database used in a facility management system according to an embodiment of the present invention. [Figure 6] Figure 6 shows an example of identification processing in a management server according to an embodiment of the present invention. [Figure 7] Figure 7 shows an example of identification processing in a management server according to an embodiment of the present invention. [Figure 8] Figure 8 shows an example of estimation processing in a management server according to an embodiment of the present invention. [Figure 9] Figure 9 shows an example of a recommended settings page displayed on an administrator terminal according to an embodiment of the present invention. [Figure 10] Figure 10 shows an example of a recommended settings page displayed on an administrator terminal according to an embodiment of the present invention. [Figure 11] Figure 11 is a flowchart showing an example of the procedure for facility management processing performed by a facility management system according to an embodiment of the present invention. [Figure 12]Figure 12 is a flowchart showing an example of the procedure for facility management processing performed by a facility management system according to an embodiment of the present invention. [Modes for carrying out the invention]

[0011] The embodiments of the present invention will be described below with reference to the attached drawings to facilitate understanding of the invention. Note that the following embodiments are merely examples of the present invention and do not limit the technical scope of the invention.

[0012] [Facility Management System 1] As shown in Figure 1, the facility management system 1 according to an embodiment of the present invention includes a management server 2, a monitoring device 3, and an administrator terminal 4. The management server 2, the monitoring device 3, and the administrator terminal 4 can communicate with each other via a communication network NW such as the Internet, LAN, WAN, or public telephone line. The facility management system 1 is installed in a facility where multiple pieces of equipment are installed. The facility is a variety of facility, such as a commercial building, a public office, a hotel, a ryokan, or a complex. The equipment is a variety of equipment, such as air conditioning equipment such as air conditioners, boilers, refrigerators, pumps, and blowers, electrical equipment such as high-pressure equipment, generators, and power supply equipment, and fire-fighting equipment such as alarms and fire extinguishers. In this embodiment, a commercial building is given as an example of the facility.

[0013] The monitoring device 3 monitors the equipment to be monitored (hereinafter also referred to as the monitored equipment) installed in each of the multiple facilities. Specifically, the monitoring device 3 uses BACnet, for example, to monitor the monitored equipment. The monitoring device 3 may be included in a so-called building automated management and control system.

[0014] The management server 2 provides a facility management service for each facility and operates a facility management service site. Specifically, the management server 2 acquires the monitoring results (measurement data, environmental data, etc.) of the monitored facilities by the monitoring device 3 and outputs a report of the monitoring results to the administrator terminal 4. In addition, the management server 2 calculates the energy consumption of the facility and each facility and outputs a report of the calculation results to the administrator terminal 4. Further, the management server 2 manages the set values of each facility, estimates the optimal set values of the facilities, and outputs a report of the estimation results to the administrator terminal 4.

[0015] In this embodiment, the management server 2 alone corresponds to the facility management system according to the present invention. However, the facility management system according to the present invention may include one or more of the components of the management server 2, the monitoring device 3, and the administrator terminal 4. For example, when the components of the management server 2, the monitoring device 3, and the administrator terminal 4 cooperate to share and execute the facility management process (see FIGS. 11 and 12) described later, a system including a plurality of components that execute the process can be regarded as the facility management system according to the present invention. For example, the management server 2, the monitoring device 3, and the administrator terminal 4 may constitute the facility management system according to the present invention. Further, the management server 2 may also have the function of the monitoring device 3. In this case, the management server 2 and the administrator terminal 4 may constitute the facility management system according to the present invention.

[0016] [Monitoring device 3] As shown in FIG. 1, the monitoring device 3 is a server including a control unit 31, a storage unit 32, an operation display unit 33, a communication I / F 34, and the like. Note that the monitoring device 3 is not limited to a single computer, and may be a computer system in which a plurality of computers cooperate to operate, or may be configured by a cloud server. In addition, various processes executed by the monitoring device 3 may be distributed and executed by one or more processors. The monitoring device 3 uses BACnet to monitor the monitored facilities installed in each of a plurality of facilities. The function of the monitoring device 3 may be included in the management server 2.

[0017] Communication I / F34 is a communication interface that connects the monitoring device 3 to the communication network NW via wired or wireless connection and performs data communication with external devices such as the management server 2 via the communication network NW in accordance with a predetermined communication protocol. Furthermore, communication I / F34 performs data communication with the monitored equipment in accordance with BACnet.

[0018] The operation display unit 33 is a user interface comprising a display unit such as a liquid crystal display or an organic EL display that displays various types of information, and an operation unit such as a mouse, keyboard, or touch panel that accepts input.

[0019] The storage unit 32 is a non-volatile storage unit such as an HDD (Hard Disk Drive) or SSD (Solid State Drive) that stores various types of information. Specifically, the storage unit 32 includes a monitoring equipment information database (hereinafter referred to as the monitoring equipment information DB) 321 and a facility data information database (hereinafter referred to as the facility data information DB) 322.

[0020] Figure 2 shows an example of a monitoring equipment information DB321 corresponding to a predetermined facility B1. The monitoring equipment information DB321 contains information such as the name (monitoring equipment name), monitoring items, units, and classification for each piece of equipment installed in facility B1 that is subject to monitoring (monitored equipment). The monitored equipment registered in the monitoring equipment information DB321 is equipped with a communication function that can use BACnet and periodically transmits data corresponding to the monitoring items to the control unit 31. Each piece of information registered in the monitoring equipment information DB321 is pre-registered by the administrator of facility B1, the service provider of the equipment management service, etc.

[0021] Figure 3 shows an example of a facility data information DB322 corresponding to a predetermined facility B1. The facility data information DB322 contains information such as the acquisition date and time, data name, detected value, and unit for each facility data acquired from the monitored equipment. The acquisition date and time is the date and time when the facility data was acquired from the monitored equipment. The data name is the name assigned to the facility data. The data name includes symbols, numbers, text information, etc. Figure 4 shows an example of the data name. There is no naming convention for the data name, and it is set by, for example, the manufacturer of the facility or equipment. The detected value is a measured value, a set value, etc. For example, if the monitored equipment is an air conditioner, the detected value is the set temperature; if the monitored equipment is a ventilation fan, the detected value is the ON or OFF setting state; and if the monitored equipment is a water heater, the detected value is the amount of water stored in the hot water tank.

[0022] Furthermore, if the monitored equipment is an environmental sensor, the detected value is the sensor's detected value. For example, if the environmental sensor is a temperature sensor that measures air temperature, the detected value is the temperature (outside air temperature). For example, if the environmental sensor is a humidity sensor that measures humidity, the detected value is the humidity (outside humidity). For example, if the environmental sensor is a sensor that measures pedestrian flow, the detected value is the number of people (number of visitors, etc.). For example, if the environmental sensor is a sensor that measures solar radiation duration, the detected value is solar radiation duration (sunshine duration).

[0023] Thus, the facility data information DB322 contains various facility data, including measurement data of equipment within facility B1 and environmental data corresponding to facility B1. The environmental data also includes data on weather, pedestrian traffic within facility B1, and solar radiation duration. The storage unit 32 stores monitoring equipment information DB321 and facility data information DB322 for each facility. In other words, the monitoring device 3 can monitor multiple facilities.

[0024] Here, the facility data includes data whose output value can be adjusted (controllable data) and data whose output value cannot be adjusted (uncontrollable data). For example, if the monitored equipment is an air conditioner, the user can adjust the temperature (room temperature), which is the output value, by setting the set temperature. In this case, the set temperature is adjustable facility data. Also, the ON / OFF setting status of the air conditioner is adjustable facility data.

[0025] For example, if the monitored equipment is a ventilation fan, the user can adjust the output values ​​(power consumption, current, etc.) by turning the fan ON or OFF. In this case, the ON / OFF setting of the ventilation fan is adjustable facility data.

[0026] For example, if the monitored equipment is a water heater, the user can adjust the output values ​​(power consumption, current, etc.) by setting the amount of water stored in the hot water tank. In this case, the amount of water stored is adjustable facility data.

[0027] In contrast, when the monitored equipment is an environmental sensor, the measured temperature (outside temperature), humidity (outside humidity), pedestrian flow, and solar radiation duration are output values ​​that depend on the environment and cannot be adjusted. Therefore, temperature (outside temperature), humidity (outside humidity), pedestrian flow, and solar radiation duration are facility data that cannot be adjusted.

[0028] The control unit 31 includes control devices such as a CPU, ROM, and RAM. The CPU is a processor that performs various arithmetic operations. The ROM is a non-volatile memory unit that stores control programs such as a BIOS and OS in advance to allow the CPU to perform various arithmetic operations. The RAM is a volatile or non-volatile memory unit that stores various information and is used as a temporary memory (work area) for the various processes performed by the CPU. The control unit 31 controls the monitoring device 3 by executing various control programs stored in advance in the ROM or memory unit 32 using the CPU.

[0029] Specifically, the control unit 31 acquires facility data such as measurement data and environmental data from each monitored piece of equipment within each facility and stores it in the storage unit 32 (see Figure 3).

[0030] Monitoring device 3 can utilize well-known technologies, such as building automated management and control systems using BACnet.

[0031] In contrast, conventional technology makes it difficult to optimize the energy consumption of equipment within a facility by utilizing various data related to the facility (adjustable data, non-adjustable data, etc.). The facility management system 1 according to this embodiment can optimize the energy consumption of a facility by utilizing various data related to the facility, as shown below.

[0032] [Management Server 2] As shown in Figure 1, the management server 2 is a server equipped with a control unit 21, a storage unit 22, an operation display unit 23, and a communication interface 24, etc. The management server 2 is not limited to a single computer; it may be a computer system in which multiple computers work together, or it may be configured as a cloud server. Furthermore, the various processes performed by the management server 2 may be distributed and executed by one or more processors.

[0033] Communication I / F24 is a communication interface that connects the management server 2 to the communication network NW via wired or wireless connection, and performs data communication with external devices such as the monitoring device 3 and administrator terminal 4 via the communication network NW in accordance with a predetermined communication protocol.

[0034] The operation display unit 23 is a user interface comprising a display unit such as a liquid crystal display or an organic EL display that displays various types of information, and an operation unit such as a mouse, keyboard, or touch panel that accepts input.

[0035] The storage unit 22 is a non-volatile storage unit such as an HDD or SSD that stores various types of information. Specifically, the storage unit 22 includes an adjustment feasibility information database (hereinafter referred to as the adjustment feasibility information DB) 221.

[0036] Figure 5 shows an example of the Adjustability Information DB221 corresponding to facility B1. The Adjustability Information DB221 contains information such as acquisition date and time, data name, detected value, unit, and adjustability for each piece of facility data (measurement data, environmental data, etc.) acquired from the monitored equipment. Each piece of information in the Adjustability Information DB221 may be the information stored in the facility data information DB322 (see Figure 3) of the monitoring device 3 with the adjustmentability information added. The adjustability is identification information (flag) that identifies whether the output value can be adjusted or not. For example, if the facility data is the set temperature of an air conditioner, the set temperature is data that can be adjusted by the user operating the air conditioner, so "1" is registered in the facility data to indicate that it can be adjusted. Also, for example, if the facility data is the ambient temperature (outside temperature) of a temperature sensor, the ambient temperature is data that cannot be adjusted, so "0" is registered in the facility data to indicate that it cannot be adjusted.

[0037] The control unit 21 identifies whether the facility data acquired from the monitoring device 3 is adjustable or not, based on the facility data, and registers the identification result in the adjustment feasibility information DB 221.

[0038] In another embodiment, part or all of the adjustment feasibility information DB221 may be stored on another server accessible from the management server 2 via the communication network NW. In this case, the control unit 21 of the management server 2 may obtain the information from the other server and execute various processes such as the facility management processes described later (see Figures 11 and 12).

[0039] Furthermore, the storage unit 22 also stores data for generating various web pages, such as the recommended settings page P1 (see Figures 9 and 10) displayed on the administrator terminal 4. In this embodiment, the control unit 21 of the management server 2 can generate the various web pages and transmit the information of those web pages to the administrator terminal 4, thereby causing the administrator terminal 4 to display the various web pages. In another embodiment, the control unit 21 of the management server 2 may transmit the data necessary to display the various web pages to the administrator terminal 4, causing the control unit 41 of the administrator terminal 4 to execute the display of the various web pages.

[0040] Furthermore, the storage unit 22 stores control programs, such as facility management programs, which cause the control unit 21 to execute the facility management processing described later (see Figures 11 and 12). For example, the facility management program is non-temporarily recorded on a computer-readable recording medium such as a CD or DVD, and is read by a reading device (not shown), such as a CD drive or DVD drive, provided by the management server 2 and stored in the storage unit 22.

[0041] The control unit 21 includes control devices such as a CPU, ROM, and RAM. The CPU is a processor that performs various arithmetic operations. The ROM is a non-volatile memory unit that stores control programs such as a BIOS and OS in advance to allow the CPU to perform various arithmetic operations. The RAM is a volatile or non-volatile memory unit that stores various information and is used as a temporary memory (work area) for the various processes performed by the CPU. The control unit 21 controls the management server 2 by executing various control programs stored in advance in the ROM or memory unit 22 using the CPU.

[0042] Specifically, as shown in Figure 1, the control unit 21 includes various processing units such as an acquisition processing unit 211, an identification processing unit 212, an estimation processing unit 213, and an output processing unit 214. The control unit 21 functions as these various processing units by executing various processes according to the facility management program using the CPU. Some or all of these processing units may be composed of electronic circuits. The facility management program may be a program that causes multiple processors to function as these processing units.

[0043] The data acquisition processing unit 211 acquires facility data, including measurement data from equipment within facility B1 and environmental data corresponding to facility B1. For example, the data acquisition processing unit 211 acquires facility data stored in the facility data information DB 322 (see Figure 3) from the monitoring device 3. In another embodiment, the data acquisition processing unit 211 may acquire the facility data directly from equipment within facility B1. The data acquisition processing unit 211 may also acquire environmental data from an organization outside facility B1. For example, the data acquisition processing unit 211 may acquire weather data (temperature, humidity, solar radiation duration, etc.) from a public organization that is appropriate for the area of ​​facility B1. The data acquisition processing unit 211 registers the information of the acquired facility data (acquisition date and time, data name, detected value, unit) in the adjustment feasibility information DB (see Figure 5). The adjustment feasibility information DB stores facility data (history data) for a predetermined time period in the past.

[0044] The identification processing unit 212 performs an identification process to determine whether each of the facility data acquired by the acquisition processing unit 211 is adjustable data or not. Specifically, the identification processing unit 212 determines whether the facility data is adjustable data or not based on at least one of the following pieces of information included in the facility data: acquisition date and time, data name, detected value (numerical value, ON / OFF), and unit.

[0045] For example, if the data name of the facility data (see Figure 4) includes the term "temperature setting" and the facility data includes the unit "degrees" or "℃", the identification processing unit 212 identifies the facility data as adjustable data. Also, for example, if the data name of the facility data includes the terms "ON" or "OFF", the identification processing unit 212 identifies the facility data as adjustable data.

[0046] Furthermore, for example, if the data name of the facility data includes the terms "outside temperature" or "outside humidity," the identification processing unit 212 identifies the facility data as data that cannot be adjusted. Furthermore, for example, if the data name of the facility data includes a unit such as the number of people (e.g., number of visitors), the identification processing unit 212 identifies the facility data as data that cannot be adjusted. Furthermore, for example, if the data name of the facility data includes the term "solar radiation duration" and the facility data includes a unit of time, the identification processing unit 212 identifies the facility data as data that cannot be adjusted.

[0047] In another embodiment, the identification processing unit 212 may identify whether the facility data is adjustable or not by performing machine learning using past facility data. For example, as shown in Figure 6, multiple past facility data are input to the learning unit A of the identification processing unit 212. The data input to the learning unit A may include data (training data) to which identification information (flags) identifying whether or not the data is adjustable is attached, and data to which such identification information is not attached. The learning unit A performs machine learning on these input data to generate a trained model that estimates whether the facility data is adjustable or not. The identification unit A of the identification processing unit 212 uses the trained model learned by machine learning to identify whether the acquired facility data is adjustable or not. The identification unit A uses the trained model to identify whether the facility data for facility B1 is adjustable or not at both the learning stage and the utilization stage.

[0048] Furthermore, well-known methods can be applied to machine learning techniques. For example, machine learning includes algorithms such as supervised learning, which uses supervised data; unsupervised learning, which uses unsupervised data; and reinforcement learning. In addition, a technique called "deep learning," which learns to extract features themselves, is used to implement these methods.

[0049] In another embodiment, the identification processing unit 212 may identify whether the facility data at a specific facility B1 is adjustable or not by using machine learning with the facility data from multiple past facilities. For example, as shown in Figure 7, the learning unit A of the identification processing unit 212 receives the past facility data from each of the multiple facilities B1, B2, ..., Bn. The data input to the learning unit A may include data (training data) that has identification information (flags) indicating whether or not it is adjustable, and data that does not have such identification information. The learning unit A uses machine learning on this input data to generate a trained model that estimates whether the facility data is adjustable or not. The identification unit A of the identification processing unit 212 uses the trained model learned by machine learning to identify whether the facility data at facility B1 is adjustable or not.

[0050] The identification processing unit 212 registers the identification result of the identification process in association with the facility data. For example, if the identification processing unit 212 identifies that the facility data is adjustable, it registers "1" in the adjustment feasibility information DB 221 (see Figure 5) to indicate that it is adjustable. Alternatively, if the identification processing unit 212 identifies that the facility data is not adjustable, it registers "0" in the adjustment feasibility information DB 221 to indicate that it is not adjustable.

[0051] The estimation processing unit 213 estimates the optimal setting value for facility data corresponding to a predetermined piece of equipment (first piece of equipment according to the present invention) based on adjustable facility data (first facility data according to the present invention) corresponding to the equipment and non-adjustable facility data (second facility data according to the present invention) related to the said facility data.

[0052] For example, the estimation processing unit 213 estimates the optimal set temperature for the air conditioner in facility B1 based on the past set temperature of the air conditioner and environmental data that affects the set temperature (outside temperature, outside humidity, pedestrian flow, sunshine duration, etc.). Also, for example, the estimation processing unit 213 estimates the optimal set state (ON / OFF) of the ventilation fan in facility B1 based on the past set state (ON / OFF) of the ventilation fan and environmental data that affects the set state (outside temperature, outside humidity, pedestrian flow, sunshine duration, etc.). Also, for example, the estimation processing unit 213 estimates the optimal set water storage volume for the water heater in facility B1 based on the past set water storage volume of the water heater and environmental data that affects the set water storage volume (outside temperature, outside humidity, pedestrian flow, sunshine duration, etc.).

[0053] Here, we will explain the specific method for estimating the optimal setting value, using the set temperature of an air conditioner as an example.

[0054] For example, as shown in Figure 8, the learning unit B of the estimation processing unit 213 receives past data on multiple adjustable and non-adjustable facility data for facility B1, as well as a target value for the past energy consumption of facility B1 (e.g., power consumption of the air conditioner). The learning unit B learns non-adjustable facility data that is related to the adjustable facility data. Specifically, the learning unit B identifies (learns) facility data among the non-adjustable facility data that have change characteristics corresponding to the change characteristics of the adjustable facility data. For example, if, in past facility data, the outside temperature, which is non-adjustable facility data, rises from D1 to D2 degrees, and the air conditioner's set temperature is lowered from T1 to T2, the learning unit B determines that the outside temperature is related to the air conditioner's set temperature. Also, for example, if, in past facility data, the flow of people (number of visitors), which is non-adjustable facility data, increases from M1 (people) to M2 (people), and the air conditioner's set temperature is lowered from T1 (degrees) to T2 (degrees), the learning unit B determines that the flow of people is related to the air conditioner's set temperature.

[0055] In this way, the estimation processing unit 213 identifies unadjustable facility data (e.g., environmental data) that have change characteristics corresponding to the change characteristics of adjustable facility data (measurement data). In the example above, the estimation processing unit 213 identifies the outside temperature among the unadjustable environmental data (outside temperature, outside humidity, pedestrian flow, solar radiation duration, etc.) that has change characteristics corresponding to the change characteristics (rise and fall) of the adjustable set temperature. The estimation processing unit 213 may identify one unadjustable facility data (e.g., outside temperature) or multiple facility data (outside temperature, pedestrian flow, etc.). Furthermore, the estimation processing unit 213 may learn the correlation between adjustable facility data and unadjustable facility data using multiple past facility data.

[0056] Furthermore, learning unit B learns the set temperature at which the air conditioner's power consumption meets the target value, based on past facility data. For example, learning unit B learns whether a set temperature meets the target power consumption based on the power consumption for each set temperature, such as the power consumption when the air conditioner's set temperature is T1, the power consumption when the air conditioner's set temperature is T2, etc. Learning unit B uses machine learning on this input data to generate a trained model that estimates the optimal set value (optimal set temperature) for adjustable data (in this case, the air conditioner's set temperature).

[0057] The estimation unit B of the estimation processing unit 213 estimates the optimal setting value for the current setting value of the equipment using a trained model learned by machine learning. The estimation unit B is input to the current adjustable and non-adjustable facility data of facility B1, and the current target value of energy consumption of facility B1. For example, the estimation unit B is input to the current set temperature of the air conditioner (adjustable facility data), current environmental data related to the set temperature (outside temperature, outside humidity, pedestrian flow, solar radiation duration, etc.) (non-adjustable facility data), and the current target value of power consumption of the air conditioner. The estimation unit B uses a trained model learned by machine learning to estimate the optimal set temperature (optimal setting value) that satisfies the target value at the current outside temperature, based on, for example, the current set temperature of the air conditioner, the current outside temperature, and the current target value of power consumption of the air conditioner.

[0058] Thus, the estimation processing unit 213 estimates the optimal setting value that satisfies the target value for the energy consumption of the equipment corresponding to the adjustable facility data, based on the correlation between the adjustable facility data and the non-adjustable facility data. The estimation processing unit 213 also estimates the aforementioned optimal setting value corresponding to the current environmental data.

[0059] The output processing unit 214 outputs the estimation results of the estimation processing unit 213. Specifically, the output processing unit 214 presents the optimal setting value to the administrator terminal 4. For example, as shown in Figure 9, the output processing unit 214 displays the recommended setting page P1 on the administrator terminal 4. The recommended setting page P1 displays equipment information such as the name of the facility, the installation location of the target equipment, the display name, and the equipment name, as well as setting information such as the current setting value, the recommended setting value, and the amount of power consumption reduction. For example, if the equipment is an air conditioner, the current setting value displays the current set temperature ("25°C"), the recommended setting value displays the optimal set temperature estimated by the estimation processing unit 213 ("21°C"), and the amount of power consumption reduction displays the expected amount of power consumption reduction ("10%") that would be achieved if the setting value were changed to the recommended value.

[0060] The output processing unit 214 may send the estimation result data to the administrator terminal 4 via email, or it may print the estimation result report from a printer (not shown).

[0061] The control unit 21 may output a setting change instruction to the target equipment when the administrator selects the "Change Settings" button on the recommended settings page P1. For example, the control unit 21 may output an instruction to the air conditioner to change the set temperature from 25 degrees to 21 degrees. Each piece of equipment may change its setting value in response to a setting change operation by the administrator, or it may change its setting value in response to a change instruction received from the control unit 21.

[0062] Figure 10 shows another example of the recommended settings page P1. The recommended settings page P1 shown in Figure 10 includes information such as the current setting value, recommended setting value, and power consumption reduction amount corresponding to each of the multiple target equipment. The control unit 21 estimates the optimal setting value for each piece of equipment within facility B1 based on the target energy consumption value (target power consumption) set for facility B1, and the current adjustable and non-adjustable facility data. The control unit 21 also calculates the power consumption reduction amount for each piece of equipment. Then, the control unit 21 calculates the achievement rate against the target power consumption based on the current power consumption of the entire facility B1 ("W1"), the target power consumption ("W0"), and the power consumption reduction amount for each piece of equipment. In this way, the control unit 21 may estimate the recommended setting values ​​for multiple pieces of equipment in facility B1 all at once.

[0063] The control unit 21 may output a setting change instruction to each target equipment when the administrator selects the "Batch Setting Change" button on the recommended settings page P1 shown in Figure 10. Each equipment may change its setting value in response to a setting change operation by the administrator, or it may change its setting value in response to a change instruction received from the control unit 21.

[0064] [Administrator terminal 4] As shown in Figure 1, the administrator terminal 4 includes a control unit 41, a storage unit 42, an operation display unit 43, and a communication interface 44, etc. The administrator terminal 4 is an information processing device such as a smartphone, tablet terminal, or personal computer.

[0065] Communication I / F44 is a communication interface for connecting the administrator terminal 4 to the communication network NW via wired or wireless connection, and for performing data communication with external devices such as the management server 2 via the communication network NW in accordance with a predetermined communication protocol.

[0066] The operation display unit 43 is a user interface comprising a display unit such as a liquid crystal display or an organic EL display that displays information such as various web pages, and an operation unit such as a mouse, keyboard, or touch panel that accepts input.

[0067] The storage unit 42 is a non-volatile storage unit such as an HDD, SSD, or flash memory that stores various types of information. For example, the storage unit 42 stores a control program such as a browser program. Specifically, the browser program is a control program that causes the control unit 41 to execute communication processing with an external device such as the management server 2 in accordance with a communication protocol such as HTTP (Hypertext Transfer Protocol). Alternatively, the browser program may be a dedicated application for executing communication processing with the management server 2 in accordance with a predetermined communication protocol.

[0068] The control unit 41 includes control devices such as a CPU, ROM, and RAM. The CPU is a processor that performs various arithmetic operations. The ROM is a non-volatile memory unit that stores control programs such as a BIOS and OS in advance to allow the CPU to perform various operations. The RAM is a volatile or non-volatile memory unit that stores various information and is used as a temporary memory (work area) for the various operations performed by the CPU. The control unit 41 controls the administrator terminal 4 by executing various control programs stored in advance in the ROM or memory unit 42 using the CPU.

[0069] Specifically, the control unit 41 functions as a browser processing unit 411 by executing various processes according to the browser program stored in the storage unit 42. The browser processing unit 411 can display a web page provided by the management server 2 via the communication network NW on the operation display unit 43 and perform browser processing to input operations on the operation display unit 43 to the management server 2. In other words, the administrator terminal 4 can function as an operation terminal for the management server 2 by the execution of the browser program by the control unit 41. Note that some or all of the processing units included in the control unit 41 may be composed of electronic circuits.

[0070] For example, when a user operation is performed on the administrator terminal 4 to request access to a predetermined URL corresponding to the facility management service site of the facility management service provided by the facility management system 1, the control unit 41 retrieves the web page data of the facility management service site from the management server 2 and displays the web page of the facility management service site on the operation display unit 43. For example, the request to access the predetermined URL can be performed by selecting from a list of pre-registered websites, selecting from search results on an information search site, or by text input. Furthermore, if a dedicated application corresponding to the management server 2 is installed on the administrator terminal 4, the web page of the facility management service site will be displayed on the operation display unit 43 when the administrator of the administrator terminal 4 performs an operation to launch the dedicated application.

[0071] For example, when the administrator of facility B1 uses the facility management service, they enter login information (ID, password) into the login page (not shown) of the facility management service site displayed on the administrator terminal 4. Once the login information is authenticated, the control unit 41 displays various web pages (for example, the recommended settings page P1 (see Figures 9 and 10)) on the operation display unit 43.

[0072] [Facility Management Processing] The facility management processes executed in the facility management system 1 will be described below with reference to Figures 11 and 12. Specifically, in this embodiment, the facility management processes are executed by the control unit 21 of the management server 2.

[0073] Furthermore, the present invention can be understood as an invention of a facility management method that performs one or more steps included in the facility management process. The one or more steps included in the facility management process described herein may be omitted as appropriate. The execution order of each step in the facility management process may differ to the extent that similar effects are produced. Moreover, although the case where the control unit 21 executes each step in the facility management process is described here as an example, a facility management method in which one or more processors distribute and execute each step in the facility management process can also be considered as another embodiment.

[0074] Figure 11 is a flowchart showing an example of the procedure for the learning stage of the estimation process that estimates the optimal setting value in the facility management process.

[0075] First, in step S11, the control unit 21 acquires historical facility data corresponding to each piece of equipment in multiple facilities. For example, the control unit 21 acquires facility data (acquisition date and time, data name, detected value, unit, etc.) from the facility data information DB322 (see Figure 3) for each facility (see Figure 7).

[0076] Next, in step S12, the control unit 21 generates a trained model by machine learning using historical facility data corresponding to each piece of equipment in multiple facilities. For example, the control unit 21 uses machine learning on facility data (training data) that has identification information (flags) indicating whether or not it is adjustable, and facility data that does not have such identification information, to generate a trained model that estimates whether the target facility data is adjustable or not (see Figure 7).

[0077] Next, in step S13, the control unit 21 acquires historical facility data corresponding to the equipment of the target facility B1. For example, the control unit 21 acquires facility data (acquisition date and time, data name, detected value, unit, etc.) from the facility data information DB322 of facility B1 (see Figure 3) (see Figure 7).

[0078] Next, in step S14, the control unit 21 uses a trained model learned by machine learning to identify whether the facility data corresponding to facility B1 is adjustable or not (see Figure 7).

[0079] Next, in step S15, the control unit 21 obtains the target value of the past energy consumption of facility B1. For example, if the target equipment is an air conditioner, the control unit 21 obtains the target value of the air conditioner's energy consumption (power consumption) (see Figure 8). The control unit 21 obtains the target value previously set by the administrator.

[0080] Next, in step S16, the control unit 21 acquires the facility data identified in step S14. For example, the control unit 21 acquires historical adjustable facility data and historical non-adjustable facility data corresponding to facility B1 (see Figure 8).

[0081] Next, in step S17, the control unit 21 generates a trained model by machine learning using the target value of energy consumption, the adjustable facility data and the non-adjustable facility data. For example, the control unit 21 generates a trained model that estimates the optimal setting value of the target equipment in facility B1 by machine learning using the target value of energy consumption corresponding to facility B1 and the adjustable and non-adjustable facility data corresponding to facility B1 (see Figure 8).

[0082] Specifically, the control unit 21 learns non-adjustable facility data (e.g., environmental data) at facility B1 that is related to adjustable facility data (measurement data). For example, the control unit 21 identifies an outdoor temperature that has change characteristics corresponding to past change characteristics (rise and fall changes) of the adjustable air conditioner set temperature, among the non-adjustable environmental data (outdoor temperature, outdoor humidity, pedestrian flow, solar radiation duration, etc.). In other words, the control unit 21 learns the correlation between adjustable facility data and non-adjustable facility data using multiple past facility data.

[0083] Furthermore, the control unit 21 learns the optimal setting value that satisfies the target value of the equipment's energy consumption based on past facility data at facility B1. For example, the control unit 21 learns whether a set temperature satisfies the target value of power consumption based on the power consumption for each set temperature of the air conditioner. The control unit 21 generates a trained model that estimates the optimal setting value (optimal set temperature) for adjustable data (e.g., the set temperature of the air conditioner) using machine learning (see Figure 8).

[0084] The trained model (optimal setting estimation model) generated during the above-mentioned training stage is stored in the memory unit 22.

[0085] Figure 12 is a flowchart showing an example of the processing procedure for the utilization stage of the estimation process that estimates the optimal setting value in the facility management process.

[0086] First, in step S21, the control unit 21 acquires the current facility data corresponding to the target facility B1. For example, the control unit 21 acquires the current facility data (acquisition date and time, data name, detected value, unit, etc.) from the facility data information DB322 (see Figure 3) corresponding to facility B1.

[0087] Next, in step S22, the control unit 21 uses the trained model generated in step S12 to identify whether the acquired current facility data is adjustable or not.

[0088] Next, in step S23, the control unit 21 obtains a target value for the current energy consumption of facility B1. For example, if the equipment in question is an air conditioner, the control unit 21 obtains a target value for the energy consumption (power consumption) of the air conditioner.

[0089] Next, in step S24, the control unit 21 acquires the facility data identified in step S22. For example, the control unit 21 acquires the current adjustable facility data and the current non-adjustable facility data corresponding to facility B1 (see Figure 8).

[0090] Next, in step S25, the control unit 21 uses the trained model (optimal setting value estimation model) generated in step S17 to estimate the optimal setting value for the target equipment in facility B1 based on the current target value of energy consumption, the current adjustable facility data and the current non-adjustable facility data (see Figure 8). For example, the control unit 21 uses the trained model to estimate the optimal setting temperature based on the current set temperature of the air conditioner, the current outside temperature, and the current target value of the air conditioner's power consumption.

[0091] Finally, in step S26, the control unit 21 outputs the estimation result. For example, as shown in Figures 9 and 10, the control unit 21 displays the recommended settings page P1 on the administrator terminal 4, and displays the estimated optimal setting temperature on the recommended settings page P1. As described above, the control unit 21 executes the facility management process.

[0092] As described above, the facility management system 1 according to this embodiment includes: an acquisition processing unit 211 that acquires facility data including measurement data of equipment within the facility and environmental data corresponding to the facility; an identification processing unit 212 that identifies whether each of the facility data acquired by the acquisition processing unit 211 is data whose output value can be adjusted by setting operations on the equipment or data whose output value cannot be adjusted by setting operations on the equipment; and an estimation processing unit 213 that estimates the optimal setting value of the first facility data based on adjustable first facility data corresponding to the first equipment and non-adjustable second facility data related to the first facility data.

[0093] With the above configuration, it is possible to estimate the optimal settings for the equipment by utilizing not only measurement data from the equipment, but also detection data from various sensors installed in the facility (such as environmental data), and environmental data acquired from outside the facility (such as sensors installed outside the facility, external organizations, and the internet) (such as weather data). Therefore, it becomes possible to optimize the energy consumption of the facility by utilizing various data related to the facility.

[0094] Furthermore, the aforementioned environmental data may include data on weather, pedestrian traffic within the facility, and solar radiation duration.

[0095] Furthermore, in the facility management system 1, the identification processing unit 212 may identify whether the facility data is adjustable or not based on at least one of the following pieces of information included in the facility data: date and time, name, numerical value, ON / OFF, and unit. This makes it easy to identify whether the facility data is adjustable or not.

[0096] Furthermore, in the facility management system 1, the identification processing unit 212 may identify whether the facility data is adjustable or not by performing machine learning using past facility data corresponding to each of the multiple facilities. This makes it possible to reliably identify whether the facility data is adjustable or not.

[0097] Furthermore, in the facility management system 1, the estimation processing unit 213 may identify facility data that has change characteristics corresponding to the change characteristics of past first facility data from among the facility data that cannot be adjusted as the second facility data. Also, the estimation processing unit 213 may learn the correlation between the first facility data and the second facility data using the past facility data acquired by the acquisition processing unit 211.

[0098] Furthermore, in the facility management system 1, the estimation processing unit 213 may estimate the optimal setting value that satisfies the target value of the energy consumption of the equipment corresponding to the first facility data, based on the correlation between the first facility data and the second facility data. Alternatively, the estimation processing unit 213 may estimate the optimal setting value corresponding to the current environmental data acquired by the acquisition processing unit 211. This makes it possible to estimate the optimal setting value according to the current environment.

[0099] Furthermore, the facility management system 1 automatically determines controllable or uncontrollable points from past and current facility data, and by comparing this with long-term energy consumption data, it proposes how to set controllable points to minimize energy consumption. The facility management system 1 also includes an identification unit that identifies controllable or uncontrollable points, and an estimation unit that learns and proposes how to set controllable points using past energy consumption data. In addition to reducing energy consumption, the estimation unit may also set parameters to maintain comfort levels (humidity, room temperature, etc.) and carbon dioxide concentration at a constant level. [Explanation of symbols]

[0100] 1: Facility Management System 2: Management Server 3: Monitoring device 4: Administrator terminal 21: Control Unit 211: Acquisition Processing Unit 212: Identification Processing Unit 213: Estimation Processing Unit 214: Output Processing Unit 411: Browser Processing Unit DB221:Adjustability information DB321: Monitoring equipment information DB322: Facility Data Information

Claims

1. An acquisition processing unit that acquires facility data including measurement data of multiple types of equipment within the facility and environmental data corresponding to the facility, An identification processing unit identifies whether each of the facility data acquired by the acquisition processing unit is data whose output value can be adjusted by user operation or data whose output value cannot be adjusted by user operation. An estimation processing unit that estimates the optimal setting value of the first facility data based on adjustable first facility data corresponding to the first equipment and second facility data from the non-adjustable facility data that has a predetermined correlation with the first facility data in past facility data, A facility management system equipped with the following features.

2. The estimation processing unit identifies the second facility data from among the facility data that cannot be adjusted, which in the past facility data affected the adjustment of the first facility data. The facility management system according to claim 1.

3. The aforementioned environmental data includes data on weather, human traffic within the facility, and solar radiation duration. The facility management system according to claim 1 or 2.

4. The identification processing unit identifies whether the facility data is adjustable or not based on at least one of the following pieces of information included in the facility data: date and time, name, numerical value, ON / OFF, and unit. A facility management system according to any one of claims 1 to 3.

5. The identification processing unit identifies whether the facility data is adjustable or not by performing machine learning using past facility data corresponding to each of the multiple facilities. A facility management system according to any one of claims 1 to 4.

6. The estimation processing unit learns the correlation between the first facility data and the second facility data using the past facility data acquired by the acquisition processing unit. A facility management system according to any one of claims 1 to 5.

7. The estimation processing unit estimates the optimal setting value that satisfies the target value for the energy consumption of the equipment corresponding to the first facility data, based on the correlation between the first facility data and the second facility data. The facility management system according to claim 6.

8. The estimation processing unit estimates the optimal setting value corresponding to the current environmental data acquired by the acquisition processing unit. The facility management system according to any one of claims 1 to 7.

9. One or more processors An acquisition step to acquire facility data including measurement data of multiple types of equipment within the facility and environmental data corresponding to the facility, An identification step is to identify whether each of the facility data acquired in the acquisition step is data whose output value can be adjusted by user operation or data whose output value cannot be adjusted by user operation. An estimation step of estimating the optimal setting value of the first facility data based on adjustable first facility data corresponding to the first equipment and non-adjustable second facility data from the facility data that has a predetermined correlation with the first facility data in past facility data, A facility management method that implements this.

10. An acquisition step to acquire facility data including measurement data of multiple types of equipment within the facility and environmental data corresponding to the facility, An identification step is to identify whether each of the facility data acquired in the acquisition step is data whose output value can be adjusted by user operation or data whose output value cannot be adjusted by user operation. An estimation step of estimating the optimal setting value of the first facility data based on adjustable first facility data corresponding to the first equipment and non-adjustable second facility data from the facility data that has a predetermined correlation with the first facility data in past facility data, A facility management program that causes one or more processors to run.

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