Driver assistance application program, driver assistance system, and driver assistance method

Abstract

To resolve the heat supply shortage of peak load machines in response to increased heat demand. [Solution] The operation support application program 100 causes the computer 10 to perform the following actions: generate predicted information 50 of virtual heat demand for each unit load time period on the day of operation using a heat demand change pattern model or a trained inference model stored in the computer 10; generate estimated information 51 of excess time periods when the virtual heat demand exceeds the heat supply capacity of the first heat source device 21 based on the predicted information 50; generate a planned value 52 of the amount of heat supplied by the second heat source device 22 necessary to satisfy the virtual heat demand 71 of the excess time period TE based on the estimated information 51; transmit the planned value 52 to the heat supply equipment 2 and cause the second heat source device 22 to perform heating operation according to the planned value 52 when the excess time period TE arrives.

Description

Technical Field

[0001] The technology disclosed in this specification relates to a driving support application program, a driving support system, and a driving support method.

Background Art

[0002] In the technical field related to industrial equipment, a system for supplying heat to load equipment such as production equipment is used. For example, Patent Document 1 discloses a hot water production system that supplies hot water heated by a first heating device including an electric heat pump and a second heating device including a combustion boiler to load equipment. In Patent Document 1, an example of operating the first heating device as a base load machine and the second heating device as a peak load machine is disclosed. In Patent Document 1, an example of performing operation control of the second heating device based on the return temperature of the hot water detected by a temperature sensor is disclosed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] The peak load machine is controlled to satisfy an excess heat demand exceeding the heat supply capacity of the base load machine. However, the heat supply by the peak load machine may be insufficient for the heat demand of the load equipment. For example, when starting the peak load machine that is in a cold state stop at the timing of detecting an increase in heat demand, there is a time lag until the heat supply catches up with the heat demand, and temporarily insufficient heat supply occurs. On the other hand, when the peak load machine is kept in a warm standby state in preparation for an increase in heat demand, continuous energy loss occurs.

[0005] The technology disclosed herein aims to resolve the heat supply shortage of peak load machines in response to increasing heat demand, and to avoid energy losses. [Means for solving the problem]

[0006] This specification provides an operation support application program. The operation support application program is an operation support application program that operates on a computer capable of sending and receiving information via a communication network with a heat supply system comprising a first heat source unit operated as a base load unit for heat demand and a second heat source unit operated as a peak load unit for heat demand. The computer performs the following actions: generates predicted information on virtual heat demand for each unit load time period on the day of operation using a heat demand change pattern model or a trained inference model stored in the computer; generates estimated information on excess time periods when the virtual heat demand exceeds the heat supply capacity of the first heat source unit based on the predicted information; generates a planned value for the heat supply amount of the second heat source unit necessary to satisfy the virtual heat demand during the excess time period based on the estimated information; and transmits the planned value to the heat supply system and causes the second heat source unit to perform heating operation according to the planned value when the excess time period arrives. [Effects of the Invention]

[0007] The technology disclosed herein can resolve the heat supply shortage of peak load machines in response to increased heat demand and avoid energy losses. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 is a schematic diagram illustrating a driver assistance system according to an embodiment. [Figure 2] Figure 2 is a schematic diagram showing the heat supply equipment and load equipment according to the embodiment. [Figure 3] Figure 3 is a hardware configuration diagram showing an information processing device according to an embodiment. [Figure 4]Figure 4 is a diagram illustrating the hierarchical structure of the information processing device according to the embodiment. [Figure 5] Figure 5 is a functional block diagram showing an information processing device according to an embodiment. [Figure 6] Figure 6 illustrates the process flow for generating and transmitting the planned heat supply amount for the second heat source device. [Figure 7] Figure 7 illustrates the process for generating forecast information for virtual heat demand. [Figure 8] Figure 8 is a diagram illustrating the planned values ​​for heat demand. [Figure 9] Figure 9 is a diagram illustrating the process for calculating the auxiliary operation period according to the embodiment. [Figure 10] Figure 10 is a diagram illustrating the processes involved in the execution of auxiliary operation. [Figure 11] Figure 11 is a schematic diagram showing a first configuration example of a heat supply system according to an embodiment. [Figure 12] Figure 12 is a schematic diagram showing a second configuration example of the heat supply equipment according to the embodiment. [Figure 13] Figure 13 is a schematic diagram showing a third configuration example of the heat supply equipment according to the embodiment. [Figure 14] Figure 14 is a schematic diagram showing a fourth configuration example of the heat supply equipment according to the embodiment. [Figure 15] Figure 15 is a flowchart illustrating the driving assistance method according to the embodiment. [Figure 16] Figure 16 is a flowchart showing the process related to auxiliary operation. [Modes for carrying out the invention]

[0009] [1] Driver assistance systems FIG. 1 is a diagram schematically showing an operation support system 1 according to an embodiment. The operation support system 1 is an operation support system for a heat supply facility 2. The operation support system 1 acquires and accumulates environmental information of the heat supply facility 2 and operation information of the heat supply facility 2. The operation support system 1 supports the operation of the heat supply facility 2 using the environmental information of the heat supply facility 2 and the operation information of the heat supply facility 2.

[0010] The facility refers to equipment installed in a building such as a factory. Equipment is a general term for machines, apparatuses, and instruments. The heat supply facility 2 refers to mechanical appliances that supply heat to a load facility LE. The heat supply facility 2 includes a plurality of heat source devices that heat a heat medium HM supplied to the load facility LE. The heat supply facility 2 supplies heat to the load facility LE by the heated heat medium HM.

[0011] The heat supply facility 2 uses a primary utility to heat a heat medium HM as a secondary utility. Examples of the primary utility input to the heat supply facility 2 include fuel (gas, oil), electricity, and raw water. The heat medium refers to an energy source or fluid necessary for industrial activities. Examples of the heat medium HM output from the heat supply facility 2 include steam, heat medium oil, hot water, and cold water.

[0012] The load facility LE uses the heat medium HM output from the heat supply facility 2. The load facility LE uses the heat medium HM as a heat source for various production processes, treatment processes, hot water supply, or air conditioning, for example.

[0013] In addition, the load facility LE may include medical mechanical appliances used in a series of processes from receiving to discharging the object to be washed and sterilized, washing mechanical appliances used in a series of processes from collecting to shipping the object to be washed, and food and beverage manufacturing mechanical appliances used in a series of processes from receiving raw materials to storing products.

[0014] As medical mechanical appliances, a washer and a sterilizer are exemplified. As washers, a vacuum boiling washer and an ultrasonic washer are exemplified. As sterilizers, a steam sterilizer and a gas sterilizer are exemplified. Medical mechanical appliances are installed in the central supply room of a medical institution.

[0015] As laundry mechanical appliances, a washing machine, a dryer, and a finishing machine are exemplified. As washing machines, a continuous washing machine, a water washing machine, and a dry cleaner are exemplified. As dryers, a gas dryer and a steam dryer are exemplified. As finishing machines, a gas roll ironer and a steam roll ironer are exemplified. Laundry mechanical appliances are installed in a laundry factory.

[0016] As food and beverage manufacturing mechanical appliances, a defroster, a cooking heater, a cooler, and a sterilizer are exemplified. As defrosters, a vacuum steam defroster, a microwave defroster, a high-frequency defroster, and a running water defroster are exemplified. As cooking heaters, a steam kneader, a steam kettle, and a saturated steam cooker are exemplified. As coolers, a vacuum cooler, a cold water cooler, and a cold air cooler are exemplified. As sterilizers, a retort sterilizer and a pasteurizer are exemplified. Food and beverage manufacturing mechanical appliances are installed in a food factory or a beverage factory.

[0017] The load equipment LE is installed in workplace 3. Workplace 3 refers to each place where the production of goods or the provision of services is carried out as a business. In workplace 3 where the production of goods etc. is carried out, a factory 4 is provided. The load equipment LE is installed in factory 4. As factory 4, a food factory, a beverage factory, a metal products factory, a plastic products factory, a textile factory, and a laundry factory are exemplified.

[0018] Note that factory 4 may not be provided in workplace 3 where services are provided. The business carried out in workplace 3 may include public health services. As public health services, a hospital, a clinic, and a health center are exemplified. Workplace 3 may include a feeding center.

[0019] In the example shown in Figure 1, a certain business operator has three business establishments 3. Business establishments 3 include the first business establishment 3A, the second business establishment 3B, and the third business establishment 3C. A factory 4 is located in the second business establishment 3B. The factory 4 located in the second business establishment 3B includes the first factory 4A and the second factory 4B. Alternatively, a factory 4 may be located in either the first business establishment 3A or the third business establishment 3C, or both.

[0020] The heat supply equipment 2 is installed in both the first factory 4A and the second factory 4B. Data collection terminals 7 are installed in both the first factory 4A and the second factory 4B. Data collection terminals 7 is a general term for devices used for data collection at the business establishment 3.

[0021] The driving support system 1 comprises a sensor group consisting of one or more environmental sensors 5 placed in the heat supply equipment 2, a controller 61 that controls the operation of the first heat source device 21 and the second heat source device 22, a communication network 8 for transmitting information, and an information processing device 6 configured to acquire environmental information detected by the sensor group and operational information generated by the controller 61 via the communication network 8.

[0022] The environmental sensor 5 detects environmental information of the heat supply equipment 2. Environmental information of the heat supply equipment 2 refers to the environmental state or conditions of the space in which the heat supply equipment 2 operates. The environmental information of the heat supply equipment 2 includes environmental information of the business establishment 3 (factory 4) where the heat supply equipment 2 is installed. The environmental information includes physical parameters of the heat supply equipment 2 and its surroundings. Some of the detection data from the environmental sensor 5 is used for the operation or control of the heat supply equipment 2. Examples of environmental sensors 5 include temperature sensors, humidity sensors, pressure sensors, water level sensors, flow rate sensors, electrical conductivity sensors (EC sensors), power sensors, distance sensors, image sensors, and force sensors.

[0023] The environmental sensor 5 is connected to the controller 61 of the heat supply equipment 2 and the controller 61 of the data collection terminal 7, respectively.

[0024] Figure 2 is a schematic diagram showing the heat supply equipment 2 and load equipment LE according to the embodiment. In the example of Figure 2, the heat supply equipment 2 and load equipment LE are installed inside the factory building (factory building) of the factory 4. The load equipment LE includes various production machinery and equipment and utilizes the heat transfer medium HM supplied from the heat supply equipment 2 during production operation. The heat supply equipment 2 heats the heat transfer medium HM according to the heat demand of the load equipment LE, and the heat transfer medium HM is, for example, water (water).

[0025] In this embodiment, the heat supply equipment 2 comprises a first heat source device 21 operated as a base load device to meet heat demand, and a second heat source device 22 operated as a peak load device to meet heat demand. The base load device operates continuously at least during load periods to supply heat. The peak load device operates when heat demand exceeds the heat supply capacity of the base load device and supplies heat to meet the excess heat demand that exceeds the heat supply capacity of the base load device. Load periods are defined as periods when heat load (heat demand) occurs, and periods when, for example, the factory 4 is shut down are excluded from load periods.

[0026] The configuration of the first heat source device 21 is not particularly limited, but in this embodiment, the first heat source device 21 has a heat pump for heating the water. The first heat source device 21 has at least one air heat source or water heat source heat pump, and may have multiple heat pumps. In the example in Figure 2, the first heat source device 21 is composed of a vapor compression type heat pump including a refrigerant evaporator 211, a refrigerant condenser 212, a refrigerant compressor 213, and an expansion valve 214. The refrigerant evaporator 211, refrigerant condenser 212, refrigerant compressor 213, and expansion valve 214 are connected by a refrigerant circulation line 215 that circulates the refrigerant. The high-temperature, high-pressure refrigerant, which is depressurized in the expansion valve 214, evaporated by endothermic reaction in the refrigerant evaporator 211, and compressed in the refrigerant compressor 213, condenses in the refrigerant condenser 212 by releasing heat. The refrigerant condenser 212 heats the water (heat transfer medium HM) by heat exchange with the high-temperature, high-pressure refrigerant. When using an intermediate heat transfer medium, the heat transfer medium HM may be heated by further heat exchange between the intermediate heat transfer medium, which has been heated in the refrigerant condenser 212, and the heat transfer medium HM.

[0027] The second heat source device 22 has a group of steam boilers that heat the water with steam. The group of steam boilers includes at least one steam boiler 221. In Figure 2, four steam boilers 221 are shown as an example for convenience, but the number of steam boilers 221 to be installed is not limited and is set according to the heat demand. The steam boilers 221 are, for example, combustion type or electric type steam boilers. A combustion type steam boiler 221 generates high-temperature, high-pressure steam from boiler water using the heat generated by the combustion of fuel, and heats the water (heat transfer medium HM) through heat exchange between the steam and the water. An electric type steam boiler 221 generates high-temperature, high-pressure steam from boiler water using the heat generated by energizing an electric heater, and heats the water (heat transfer medium HM) through heat exchange between the steam and the water.

[0028] The heat supply equipment 2 includes a water tank 23 for storing water (water), which is the heat transfer medium HM. The water tank 23 stores water heated by the first heat source device 21 and the second heat source device 22. The water tank 23 and the first heat source device 21 are connected by a water line 24. The water tank 23 and the second heat source device 22 are connected by a steam line 25. In this specification, "line" refers to any line through which fluids can flow, such as a flow path, route, or pipeline.

[0029] The water supply line 24 is a passage for circulating water, which is the heat transfer medium HM. Water heated by the first heat source device 21 is supplied to the water supply tank 23 via the water supply line 24. The steam line 25 is a passage for circulating high-temperature steam generated by the steam boiler group. In this configuration, a steam heater is installed inside the water supply tank 23 to exchange heat between steam and water, and the water stored in the water supply tank 23 is heated by steam from the second heat source device 22.

[0030] Heated water is stored in the water tank 23. The water line 24 connects the water tank 23 to the load equipment LE. The water (heat transfer medium HM) stored in the water tank 23 is supplied to the load equipment LE via the water line 24. The load equipment LE either uses the supplied water as is or uses the heat extracted from the water. The water line 24 may be equipped with a pump to circulate the heat transfer medium HM.

[0031] The environmental sensor 5 is installed in the heat supply equipment 2. The environmental sensor 5 can be installed in one or more of the heat source devices (first heat source device 21, second heat source device 22), the water supply line 24, or the water supply tank 23. The environmental sensor 5 installed in the heat supply equipment 2 includes a temperature sensor. The environmental sensor 5 may also be installed in the load equipment LE.

[0032] The controller 61 of the heat supply equipment 2 has the function of controlling the operation of the heat supply equipment 2 and controlling data collection. The controller 61 is mainly used for autonomous operation control of the heat source devices (first heat source device 21, second heat source device 22). The controller 61 of the heat supply equipment 2 is connected to environmental sensors 5 installed in the heat source devices, water lines 24, or water tanks 23. The controller 61 of the heat supply equipment 2 may also be configured as part of a data collection terminal 7 that is specialized for collecting information from the environmental sensors 5.

[0033] As shown in Figure 1, the controller 61 is incorporated into the heat supply equipment 2, the load equipment LE, and the data acquisition terminal 7. Examples of the controller 61 include a microcomputer 61A and a programmable logic controller 61B (PLC). The microcomputer 61A is an example of the controller 61 incorporated into the data acquisition terminal 7.

[0034] The controller 61 of the heat supply equipment 2 uses environmental information collected from the environmental sensor 5 to control the operation of the heat supply equipment 2 and records it for operational management.

[0035] The controller 61 of the data collection terminal 7 is connected to each of the multiple environmental sensors 5 scattered throughout the business premises 3. The controller 61 of the data collection terminal 7 is connected to multiple environmental sensors 5 of different types.

[0036] The controller 61 generates operating information for the heat source devices (first heat source device 21, second heat source device 22). The controller 61 may also generate operating information for the heat source devices based on the detection data of the environmental sensor 5.

[0037] [2] Hardware configuration of the information processing device As shown in Figure 1, the driver assistance system 1 has a plurality of information processing devices 6. The information processing devices 6 include a controller 61, an edge computer 62, a gateway 63, a guest computer 64, and a host computer 65.

[0038] Figure 3 is a hardware configuration diagram showing an information processing device 6 according to an embodiment. The information processing device 6 includes a computer 10. The controller 61, edge computer 62, gateway 63, guest computer 64, and host computer 65 each include the computer 10. The computer 10 has a processor 11, a storage device 12, a communication interface 13, and an input / output interface 14. The information processing device 6 also has a power supply (not shown).

[0039] The processor 11 includes a CPU (Central Processing Unit). The processor 11 may also include a GPU (Graphics Processing Unit). The storage device 12 includes a recording medium on which computer programs and data are recorded in a readable format by the processor 11. The storage device 12 includes onboard system memory such as RAM (Random Access Memory) or ROM (Read Only Memory), high-capacity flash memory such as an SD card or USB memory, and high-capacity storage such as an HDD (Hard Disk Drive) or SSD (Solid State Drive).

[0040] The communication interface 13 communicates via the communication network 8. Computer 10 sends data to an external computer via the communication network 8. Computer 10 receives data from an external computer via the communication network 8. Computer 10 connects to an external device via the input / output interface 14.

[0041] The communication network 8 is a general term for communication paths and devices that enable communication so that multiple computers 10 can send and receive information. Examples of communication networks 8 include local area networks (LANs), wide area networks (WANs), and commercial networks such as the Internet. A local area network may be a wired LAN or a wireless LAN. A wide area network may include mobile lines or satellite communication lines.

[0042] The storage device 12 stores various software programs. The storage device 12 stores a driver assistance application program 100 according to an embodiment. The processor 11 reads the software program from the storage device 12, loads it into system memory, and executes processing according to the software program. That is, the processor 11 can be considered to have multiple functional units. The functions of the processor 11 are realized by the software program. The software program may be distributed to the computer 10 via the communication network 8.

[0043] A software program that implements a specific function on a computer is called an application or engine (hereinafter referred to as "application, etc."), and the functional unit of an application, etc. is called a module. An application, etc. may be installed on a computer as a single software package containing all functions, but it is preferable to install it on a computer as individual software modules, each containing a functional unit. When the functional units of an application, etc. are modularized, updates become easier when functional modifications are made. An application that runs on an edge computer 62 is sometimes called an edge application.

[0044] The environmental sensor 5 is connected to the input / output interface 14 of the controller 61. Multiple environmental sensors 5 are connected to one controller 61. The controller 61 collects environmental information from the environmental sensors 5 in real time. The communication interface 13 of the controller 61 transmits real-time environmental information and real-time operational information to the edge computer 62 via the communication network 8 (LAN).

[0045] The heat source device controller 61 can function not only as a local controller for the heat source devices (first heat source device 21, second heat source device 22), but also as a system controller for controlling peripheral equipment (e.g., water pumps, water supply valves, etc.).

[0046] The edge computer 62 is installed in factory 4. One or more edge computers 62 are installed in each factory 4. The communication interface 13 of the edge computer 62 communicates with each of the multiple controllers 61 belonging to factory 4 where the edge computer 62 is located, via the communication network 8 (LAN). The edge computer 62 receives environmental information and operational information from the controllers 61 via the communication network 8.

[0047] The edge computer 62 has approximately 5GB of onboard memory as storage device 12 so as to be able to store a sufficient amount of information. The edge computer 62 may also have an AI engine (Neural Network Processing Unit: NPU) so as to be able to perform the training and inference phases in machine learning.

[0048] Gateway 63 constitutes a connection node between the local area network and the internet, and has performance and specifications equivalent to that of the edge computer 62. Gateway 63 is installed at business establishment 3. One or more gateways 63 are installed at each business establishment 3. The communication interface 13 of gateway 63 communicates with each of the multiple edge computers 62 belonging to business establishment 3 where gateway 63 is located, via the communication network 8 (LAN). Gateway 63 receives environmental information and operational information from the edge computers 62 via the communication network 8. If the factory 4 located at business establishment 3 is a single building, the edge computer 62 and gateway 63 may be integrated and configured as a single computer.

[0049] The guest computer 64 is located outside of the business premises 3. For example, the guest computer 64 is installed at a regional base of a service provider that undertakes tasks such as monitoring the status and maintenance of the heat supply equipment 2 installed at business premises 3. One guest computer 64 is installed at each management base. The guest computer 64 includes a local server. The communication interface 13 of the guest computer 64 communicates with the gateway 63 belonging to business premises 3 via the communication network 8 (Internet). The guest computer 64 receives environmental information and operational information from the gateway 63 via the communication network 8. If a guest computer 64 is not installed, the gateway 63 and the host computer 65 (described later) will be connected via the communication network 8.

[0050] The host computer 65 is located outside of the business premises 3. For example, the host computer 65 is installed at the central hub of a service provider. The host computer 65 includes a cloud server. The communication interface 13 of the host computer 65 communicates with each of the multiple guest computers 64 via the communication network 8 (Internet). The host computer 65 receives environmental information and operational information from the guest computers 64 via the communication network 8.

[0051] [3] Hierarchical structure of information processing equipment Figure 4 is a diagram illustrating the hierarchical structure of the information processing device 6 according to the embodiment. The multiple information processing devices 6 have a hierarchical structure that transmits environmental information detected by the environmental sensor 5 and operational information generated by the controller 61 from the downstream side to the upstream side. Of the multiple information processing devices 6, the controller 61 to which the environmental sensor 5 is connected is the most downstream (lower layer, lower level) information processing device 6, followed by the edge computer 62 as the next downstream information processing device 6, followed by the gateway 63 as the next downstream information processing device 6, followed by the guest computer 64 as the next downstream information processing device 6, and the host computer 65 as the most upstream (upper layer, higher level) information processing device 6.

[0052] The information processing devices 6 are connected to each other via a communication network 8. Inside the building, a local area network is used as the communication network 8, while outside the building, a commercial wide area network such as an internet connection or a mobile network is used as the communication network 8.

[0053] Environmental information is detected by the environmental sensor 5. The controller 61, which is a lower-level information processing device in the hierarchical structure, acquires the environmental information from the environmental sensor 5. The environmental information detected by the environmental sensor 5 and collected by the controller 61 is transmitted from the controller 61 to the edge computer 62 via the communication network 8. Operational information generated by the controller 61 is also transmitted from the controller 61 to the edge computer 62 via the communication network 8. The environmental information and operational information transmitted to the edge computer 62 are then transmitted from the edge computer 62 to the gateway 63 via the communication network 8. The environmental information and operational information transmitted to the gateway 63 are then transmitted from the gateway 63 to the guest computer 64 via the communication network 8. The environmental information and operational information transmitted to the guest computer 64 are then transmitted from the guest computer 64 to the host computer 65 via the communication network 8.

[0054] The controller 61 is a lower-level information processing unit in the hierarchical structure. The edge computer 62, gateway 63, and guest computer 64 are intermediate information processing units in the hierarchical structure. The host computer 65 is a higher-level information processing unit in the hierarchical structure.

[0055] The lower-level information processing unit functions as an IoT device to which the environmental sensor 5 is connected. The lower-level information processing unit can transmit various environmental and operational information to the intermediate information processing unit. The intermediate information processing unit functions as a relay between the lower-level information processing unit and the higher-level information processing unit. The intermediate information processing unit can receive various environmental and operational information from the lower-level information processing unit and transmit various environmental and operational information to the higher-level information processing unit. The higher-level information processing unit can receive various environmental and operational information from the intermediate information processing unit.

[0056] [4] Software configuration of the information processing device Figure 5 is a functional block diagram showing an information processing device 6 according to an embodiment. The information processing device 6 includes an information processing module 31, a prediction information generation module 32, an estimation information generation module 33, a planned value generation module 34, a planned value transmission module 35, an information storage platform 36, and a database 37. The database 37 may be a group of databases that handle a wide variety of information, or it may be a component of the information storage platform 36. In the example of Figure 5, the information processing device 6 further includes a heat storage amount calculation module 38, an additional information generation module 39, an auxiliary operation execution module 40, and a UI provision module 41. The information processing device 6 does not necessarily have to include the heat storage amount calculation module 38, the additional information generation module 39, the auxiliary operation execution module 40, and the UI provision module 41.

[0057] A user terminal 45 is connected to an information processing device 6. Examples of user terminals 45 include personal computers, tablet devices, and smartphones. The user terminal 45 includes a display device such as a liquid crystal display or an organic EL display.

[0058] The multiple information processing devices 6 (61, 62, 63, 64, 65) each have, in one or more layers, an information processing module 31, a prediction information generation module 32, an estimated information generation module 33, a planned value generation module 34, a planned value transmission module 35, an information storage platform 36, a database 37, a heat storage amount calculation module 38, an additional information generation module 39, an auxiliary operation execution module 40, and a UI provision module 41. That is, each of the information processing module 31, prediction information generation module 32, estimated information generation module 33, planned value generation module 34, planned value transmission module 35, information storage platform 36, database 37, heat storage amount calculation module 38, additional information generation module 39, auxiliary operation execution module 40, and UI provision module 41 can be a functional unit in one or more layers of the multiple information processing devices 6 (61, 62, 63, 64, 65).

[0059] Some or all of these functional units are realized by causing the computer 10 to perform information processing according to the driving support application program 100 according to the embodiment. That is, the driving support application program 100 has program modules for operating the computer 10 as an information processing module 31, a prediction information generation module 32, an estimated information generation module 33, a planned value generation module 34, a planned value transmission module 35, a heat storage amount calculation module 38, an additional information generation module 39, an auxiliary operation execution module 40, and a UI provision module 41. The computer 10 executes the respective program modules corresponding to the information processing module 31, prediction information generation module 32, estimated information generation module 33, planned value generation module 34, planned value transmission module 35, a heat storage amount calculation module 38, an additional information generation module 39, an auxiliary operation execution module 40, and a UI provision module 41, thereby realizing each information processing as a functional unit.

[0060] In one example, it is preferable that the prediction information generation module 32, the estimation information generation module 33, the planned value generation module 34, and the planned value transmission module 35 be functional units of the edge computer 62. It is preferable that the heat storage amount calculation module 38, the additional information generation module 39, and the auxiliary operation execution module 40 be functional units of the edge computer 62. It is preferable that the information processing module 31 be functional unit of the edge computer 62 or gateway 63, and it is preferable that the UI provision module 41, the information storage platform 36, and the database 37 be functional units of the host computer 65. When the operation support system 1 is completed within the factory building (factory building) of the factory 4 at the request of the operations manager of the business establishment 3, all of the modules, platforms, and databases may be functional units of the edge computer 62.

[0061] <4-1> Information Processing Module The information processing module 31 performs predefined information processing on the acquired environmental information and operational information. The information processing performed by the information processing module 31 includes, for example, batch processing to adjust time-series environmental information and operational information to the required time granularity. The information processing performed by the information processing module 31 also includes, for example, grouping processing to integrate multiple different types of environmental information and operational information into an information set linked to the hierarchical level of industrial activity.

[0062] <4-1-1> Generation process of environmental information and operational information The information processing module 31 acquires and stores environmental information from the environmental sensor 5 at predetermined sampling intervals. The information processing module 31 has functions such as A / D conversion to convert analog signals from the environmental sensor 5 into digital signals, substitution of A / D values ​​with measurement sample values, selection of measurement sample values, moving average function of measurement sample values, and period or frequency measurement function of pulse signals, and uses these functions to calculate confirmed measurement values ​​in real time.

[0063] The information processing module 31 acquires and stores real-time operational information from the controller 61 at predetermined sampling intervals. For example, the controller 61 transmits an "operating" signal when the heat source device is operating and a "stopped" signal when it is stopped. The information processing module 31 uses the "operating" signal received via the input / output interface 14 to measure the uptime (actual operating time information) of the heat source device. The information processing module 31 also uses the "stopped" signal received via the input / output interface 14 to measure the downtime (non-operating time information) of the heat source device.

[0064] The time granularity of real-time environmental information and real-time operational information depends on the sampling interval or recording interval, and is generally quite fine (for example, the latest values ​​are updated at intervals of 10ms to 1s). The information processing module 31 transmits the environmental information, along with an identification number (measurement item ID, device ID, location ID, etc.) and the update time, to the higher-level information processing device 6.

[0065] <4-1-2> Batch Processing Real-time environmental information and real-time operational information are time-series data that are generated sequentially over time in the information processing module 31. Batch processing refers to the process of adjusting the time-series environmental information and operational information to the required time granularity. Time granularity is an indicator that represents the degree of fineness of time, and can be selected from, for example, seconds, minutes, hours, or days.

[0066] <4-1-3> Grouping process Grouping refers to the process of integrating multiple types of environmental and operational information (environmental information, batch environmental information, operational information, batch operational information) into an information set linked to the hierarchical level of industrial activity. As shown in Figure 4, the hierarchical level of industrial activity includes one or more levels from among the machine level, machine group level, cell level, line level, building level, and business establishment level.

[0067] <4-2> Information Storage Platform The information storage platform 36 stores various types of information, such as numerical data and images, and also provides a foundational environment for operating software (engines, applications) and hardware. The information storage platform 36 is composed of, for example, an operating system and a database, enabling centralized management of diverse big data and facilitating the smooth processing and utilization of information.

[0068] The information storage platform 36 stores environmental information and operational information that have undergone prescribed information processing by the information processing module 31, as well as various registration information registered via the input device.

[0069] Environmental information includes various types of information used to calculate heat demand. Environmental information includes, for example, the temperature and flow rate of the heat transfer medium HM supplied to the load equipment LE. Operational information includes various types of information used to calculate the heat supply amount of each heat source device (first heat source device 21 and second heat source device 22) of the heat supply equipment 2. Operational information includes, for example, one or more of the following: heat output information, operating frequency information, and number of operating units. Heat output information is information on the amount of heat that the heat source device provides (outputs) to the heat transfer medium HM. Heat output information can be expressed, for example, as the amount of heat output per unit time (J) or as an index value indicating the amount of heat output. When the flow rate of the heat transfer medium HM (water) is kept constant, the temperature of the heat transfer medium HM (hot water outlet temperature) can be used as the index value for heat output information. Operating frequency information is information indicating how often the heat source device performs heat output operation. Operating frequency information can be expressed, for example, as the number of transitions from a stopped state to an operating state that occur per unit time (number of starts). The operating unit information indicates the number of heat source devices (e.g., steam boilers 221) operating simultaneously. The operating unit information may be the numerical value of the number of operating heat source devices themselves, or it may be expressed as an index value, such as the ratio of the operating unit to the base unit. For example, if the total number of steam boilers 221 of the second heat source device 22 is the base unit, the ratio of the operating unit will be the operating rate of the second heat source device 22. Note that the operating rate referred to here is the instantaneous operating rate and is distinct from the time operating rate, which is the ratio of operating time to load time.

[0070] Thus, the computer 10 (information processing device 6) is configured to acquire environmental information detected by the sensor group and operational information generated by the controller 61 via the communication network 8, and also has an information storage platform 36 for storing the acquired environmental information and operational information.

[0071] <4-3> Predictive Information Generation Module Figure 6 is a diagram illustrating the process flow for generating and transmitting the planned value 52 of the heat supply amount of the second heat source device 22. Figure 7 is a diagram illustrating the process for generating predicted information 50 of virtual heat demand. As shown in Figures 6 and 7, the prediction information generation module 32 uses the heat demand prediction model 70 stored in the computer 10 to generate predicted information 50 of virtual heat demand for each unit load time period on the day of operation.

[0072] The prediction model 70 is a heat demand change pattern model or a trained inference model generated by utilizing environmental information stored in the information storage platform 36. The information storage platform 36 collects and stores, for example, heat demand data for each unit load time period (e.g., every hour) throughout the year at the managed object (e.g., factory 4 in Figure 2).

[0073] <4-3-1> Model of changes in heat demand The heat demand change pattern model is a collection of statistical values ​​for heat demand for each unit load time period of the managed area. The heat demand change pattern model is created by applying statistical processing to the environmental information stored in the information storage platform 36.

[0074] A model of the pattern of changes in heat demand can be created, for example, by following these steps. First, the year is divided into winter (December-February), intermediate season (March-May), summer (June-August), and intermediate season (September-November), and representative values ​​are extracted from 12 heat demand data points for the same time period and day of the week for each period. Since the distribution of heat demand data is biased and affected by outliers, the representative values ​​to be extracted are considered to be most appropriate in the order of mode, median, and mean.

[0075] Arrange the representative values ​​for each day of the week in order of time of day to create a pattern of change in representative values ​​for one week. Create this pattern of change in representative values ​​for one week for each of the four periods that make up one year.

[0076] The extracted representative values ​​are predicted values ​​of heat demand for a given period, a given day of the week, and a given unit load time period. In this specification, these predicted values ​​are referred to as "virtual heat demand." The change pattern of representative values ​​for one week for each period is calculated by determining the change pattern of the daily virtual heat demand for each period, broken down by day of the week. The heat demand change pattern model includes change pattern data for the daily virtual heat demand for each unit load time period in each of the four periods, broken down by day of the week. Therefore, once the period and day of the week to which the operating day belongs are specified, the virtual heat demand for each unit load time period on the operating day can be estimated from the change pattern data.

[0077] The length and timing of each period used to divide the year may vary depending on the region where the managed data is located. Furthermore, it is preferable to update the heat demand change pattern model by integrating and replacing data using additional historical information each year.

[0078] <4-3-2> Pre-trained inference model for heat demand The pre-trained inference model for heat demand is an inference model created to output a predicted value of heat demand (virtual heat demand) using machine learning based on environmental information stored in the information storage platform 36. The pre-trained inference model is created, for example, to output the virtual heat demand for the day of operation using regression analysis.

[0079] The training data used to create (learn) a pre-trained inference model consists of a dataset where features are used as explanatory variables and target labels are used as the target variable. Specifically, the training data is composed of three features: lunar phase, day of the week, and load time period, with the actual heat demand for each lunar phase, day of the week, and load time period identified by these features as the target labels. The training data includes a sufficient number of sample data for actual heat demand for each lunar phase, day of the week, and load time period. The actual heat demand is calculated from environmental information measured on-site using environmental sensors 5 (in this case, temperature sensors and flow sensors). The actual heat demand for each lunar phase, day of the week, and load time period is calculated based on the environmental information stored in the information storage platform 36.

[0080] The first explanatory variable, lunar phase, is defined as a variable from 1 to 12, for example, representing January to December. The second explanatory variable, day of the week, is defined as a variable from 1 to 7, for example, representing Sunday to Saturday (Thursday would be 5). The third explanatory variable, load time period, is defined as a variable from 1 to 24, dividing 24 hours into 1-hour intervals (0:00-1:00 is 1, 1:00-2:00 is 2, ..., 23:00-24:00 is 24).

[0081] The dependent variable, actual heat demand, may be expressed as either the absolute value of heat (in J) or the relative value of heat (in %). When using relative values, the sample data of actual heat demand is expressed as a percentage, with the maximum heat demand that can be generated by the load equipment LE set to 100%.

[0082] The trained inference model, through machine learning using the aforementioned training data, has acquired a regression equation that outputs a corresponding virtual heat demand (estimated heat demand) for any set of explanatory variables (lunar phase, day of the week, and load time period).

[0083] By inputting three explanatory variables for the day of operation into the created trained inference model, it becomes possible to predict the virtual heat demand for each unit load time period. If the virtual heat demand is output as a percentage, it can be converted to an energy value (in J) by multiplying that percentage value by the maximum heat demand that can be generated by the load equipment LE. Arranging the predicted virtual heat demand data over time yields data equivalent to a heat demand change pattern model.

[0084] Note that the explanatory variables (input variables) of the trained inference model are not limited to the date and time information mentioned above.

[0085] The explanatory variables (input variables) may, for example, be the output information of the load equipment LE per unit load time. For example, if the load equipment LE is production machinery, information on the production quantity per unit load time may be used as the explanatory variable. In this case, the training data is composed of actual values ​​of the production quantity per unit load time (e.g., per hour) as features, and the actual heat demand required for the production quantity identified by these features as the training label. Through machine learning, a trained inference model is obtained that outputs a corresponding virtual heat demand (estimated value of heat demand) for the input of explanatory variables (production quantity per unit load time). By inputting the planned values ​​of the production quantity for each unit load time period on the day of operation into the trained inference model, it becomes possible to predict the virtual heat demand for each unit load time period.

[0086] Furthermore, the explanatory variables (input variables) may be, for example, operating information of the load equipment LE during a unit load time. For example, information such as the equipment load rate and power load rate of the load equipment LE during a unit load time may be used as explanatory variables. The equipment load rate is the ratio (percentage) of the amount of processing when the load equipment LE operates at the actual load for one hour to the amount of processing when it operates at the maximum load for one hour. The power load rate is the ratio (percentage) of the amount of power consumed when the load equipment LE operates at the actual load for one hour to the amount of power consumed when it operates at the maximum load for one hour. In this case, the training data is constructed using the actual values ​​of the equipment load rate or power load rate as features, and the actual heat demand generated at the equipment load rate or power load rate identified by those features as training labels. Through machine learning, a trained inference model is obtained that outputs the corresponding virtual heat demand (estimated value of heat demand) for each input of explanatory variables (equipment load rate or power load rate). By inputting the planned values ​​of the equipment load rate or power load rate for each unit load time period on the day of operation into the trained inference model, it becomes possible to predict the virtual heat demand for each unit load time period.

[0087] <4-3-3> Predictive Information The forecast information 50 is information on the virtual heat demand for each unit load time period on the day of operation. The forecast information generation module 32 generates the forecast information 50 of the virtual heat demand for each unit load time period on the day of operation using the heat demand forecast model 70 (i.e., the heat demand change pattern model or the trained inference model). That is, the forecast information generation module 32 obtains the virtual heat demand for each unit load time period on the day of operation from the change pattern model based on the period and day of the week to which the day of operation belongs. Alternatively, the forecast information generation module 32 obtains the virtual heat demand for each unit load time period on the day of operation by inputting information on explanatory variables for the day of operation into the trained inference model.

[0088] The forecast information 50 allows for the prediction of changes in virtual heat demand for each unit load time period on the day of operation, before such changes occur. In other words, the forecast information 50 allows for the prediction of the magnitude (heat quantity [J]) of heat demand at the load equipment LE to be determined in advance, at which load time period.

[0089] The prediction model 70 may include both a heat demand change pattern model and a trained inference model. Furthermore, the prediction model 70 may include multiple types of change pattern models and multiple types of trained inference models. If the prediction model 70 includes multiple models, the driver assistance application program 100 (prediction information generation module 32) may have a function to select the model to be used to generate the virtual heat demand prediction information 50.

[0090] <4-4> Predictive Information Generation Module As shown in Figure 6, the prediction information generation module 33 generates prediction information 51 of the excess time period in which the virtual heat demand exceeds the heat supply capacity of the first heat source device 21, based on the prediction information 50.

[0091] The excess period is the time period within the load period when the heat demand (virtual heat demand) exceeds the heat supply capacity of the first heat source device 21. In other words, the excess period is the time period when the operation of the second heat source device 22 (steam boiler group) is required. The heat supply capacity of the first heat source device 21 is, for example, the amount of heat that the first heat source device 21 can supply during a unit load period, and is pre-registered in the database 37 as part of the specifications of the first heat source device 21. The operation support application program 100 (estimated information generation module 33) may include an optional setting function for setting the heat supply capacities of the first heat source device 21 and the second heat source device 22.

[0092] The prediction information generation module 33 compares the virtual heat demand for each unit load time period included in the prediction information 50 with the heat supply capacity of the first heat source device 21, and extracts the time periods in which the virtual heat demand is greater than the heat supply capacity of the first heat source device 21. The prediction information generation module 33 generates prediction information 51 that includes information on all excess time periods on the day of operation. The prediction information 51 makes it possible to know in advance which unit load time periods will experience excess heat demand on the day of operation.

[0093] <4-5> Planned Value Generation Module As shown in Figure 6, the planned value generation module 34 generates a planned value 52 for the amount of heat supplied by the second heat source device 22, which is necessary to satisfy the virtual heat demand 71 during the excess time period TE, based on the estimated information 51.

[0094] Figure 8 is a diagram illustrating the planned value 52 for heat demand. In Figure 8, the concept of change in virtual heat demand 71 is shown graphically, with the vertical axis of the graph representing heat demand (heat quantity [J]) and the horizontal axis representing time. The planned value generation module 34 generates the planned value 52 for heat supply from the predicted information 50 for virtual heat demand 71, the heat supply capacity 72 of the first heat source device 21, and the estimated information 51 for the excess time period TE. In each unit load time period belonging to the excess time period TE, the virtual heat demand 71 exceeds the heat supply capacity 72 of the first heat source device 21. In each unit load time period, the value obtained by subtracting the heat supply capacity 72 of the first heat source device 21 from the virtual heat demand 71 is the amount of heat supply that is insufficient in that unit load time period (the excess heat demand that exceeds the heat supply capacity 72). The planned value generation module 34 generates the difference between the virtual heat demand amount 71 and the heat supply capacity 72 of the first heat source device 21 for each unit load time period belonging to the excess time period TE, as the planned value 52 for the heat supply amount of the second heat source device 22.

[0095] Therefore, the planned value 52 for the heat supply represents the amount of heat that the second heat source device 22 should generate to satisfy the virtual heat demand 71 in each unit load time period belonging to the excess time period TE. In this embodiment, the planned value 52 includes the specific enthalpy and mass of the steam generated by the steam boiler group. The amount of heat supply (energy) required by the steam boiler group during the excess time period TE is the specific enthalpy of the steam (total heat, unit: J / kg) multiplied by the mass of the steam (unit: kg). Since the specific enthalpy changes with the pressure of saturated steam, the amount of heat supply can be adjusted by manipulating the operating pressure and evaporation rate of the steam boiler 221.

[0096] Furthermore, the planned value 52 for heat supply includes the number of operating steam boilers in the steam boiler group and the combustion rate of each individual steam boiler. The operating pressure of each steam boiler 221 constituting the steam boiler group can be set individually. On the other hand, the evaporation rate of the steam boilers 221 can be controlled by increasing or decreasing the number of operating steam boilers in the steam boiler group and adjusting the combustion rate of each steam boiler 221. As a result, by adjusting the number of operating boilers and the combustion rate in accordance with the planned value 52, the second heat source device 22 can generate the necessary amount of heat supply to satisfy the virtual heat demand 71 without excess or deficiency.

[0097] <4-6> Planned Value Transmission Module As shown in Figure 6, the planned value transmission module 35 transmits the planned value 52 to the heat supply equipment 2, causing the second heat source device 22 to perform heating operation according to the planned value 52 when the excess time period TE arrives. The planned value transmission module 35 transmits the planned value 52 to the controller 61 via the communication network 8. The controller 61 starts the second heat source device 22 when the excess time period TE arrives (preferably starting the second heat source device 22 at a time retroactive to the time required for warm-up operation from the start of the excess time period TE), and generates a heat supply amount under operating conditions according to the planned value 52. As a result, the second heat source device 22 operates to supply an amount of heat corresponding to the difference (see hatched area) between the heat supply capacity 72 of the first heat source device 21 and the virtual heat demand 71 shown in Figure 8 during the excess time period TE.

[0098] Thus, in this embodiment, the second heat source device 22 is not started only after an increase in heat demand is detected by the environmental sensor 5. Instead, the time change of the virtual heat demand 71 on the day of operation is predicted based on the history information of the actual heat demand, and the amount of heat supplied by the peak load device (second heat source device 22) is planned after narrowing down the excess time period TE. Then, the second heat source device 22 is operated according to the pre-generated planned value 52, so the delay in response to the increase in heat demand and the shortage of heat supply caused by the delay in response are eliminated. In addition, there is no need to keep the peak load device in a hot standby state, so no energy loss occurs.

[0099] <4-7> Heat Storage Amount Calculation Module Figure 9 is a diagram illustrating the process for calculating the auxiliary operation period 75 according to the embodiment. The heat storage amount calculation module 38 calculates the amount of heat stored 73 of the water (i.e., heat transfer medium HM) stored in the water tank 23 based on information from the environmental sensor 5 installed in the heat supply equipment 2. As shown in Figure 9, the amount of heat stored 73 of the water corresponds to the amount of heat that can be supplied from the water tank 23 to the heat demand of the load equipment LE at that time. The amount of heat stored 73 of the water is determined by the amount of water stored in the water tank 23 and the water temperature, assuming that the physical properties of the water (heat transfer medium HM) are known. The amount of water stored can be converted using the water level in the water tank 23. If the water temperature is a predetermined value (set value), the amount of heat stored 73 of the water can be determined from the water level information. An example of an environmental sensor 5 that provides water level information is a water level sensor installed in the water tank 23. The water temperature in the water tank 23 may also be measured by a temperature sensor as the environmental sensor 5. The heat storage amount calculation module 38 calculates the amount of heat stored in the water supply, 73, from the information of the environmental sensor 5, which includes water level information.

[0100] <4-8> Additional Information Generation Module Figure 10 is a diagram illustrating the process involved in the execution of auxiliary operation. As shown in Figure 10, the additional information generation module 39 generates additional information for the low-load period TL, when the actual heat demand falls below a predetermined value, based on the operation plan of the load equipment LE. The predetermined value is set to a value lower than the heat supply capacity 72 of the first heat source device 21. In other words, during the low-load period TL, the actual heat demand of the load equipment LE falls below the heat supply capacity 72 of the first heat source device 21, and there is a margin in the heat supply capacity 72 of the first heat source device 21.

[0101] The low-load period TL includes the low-productivity period during which the standby ratio of production machinery and equipment exceeds a predetermined ratio within the daily operating hours of Factory 4, as well as the downtime period during which the production line is stopped. The standby ratio of production machinery and equipment is the ratio of the number of standby units to the total number of production machinery and equipment installed in Factory 4. Specifically, the downtime period corresponds to the period from the end of the day when the production line is stopped to the start of the next day when the production line starts operating (start time). The downtime period can also be described as the no-load period during which no heat load is generated from load equipment such as production machinery and equipment. In other words, the low-load period TL is a concept that includes the period during which the heat load is lower than a predetermined value and the period during which no heat load is generated (becomes zero).

[0102] The additional information generation module 39 identifies low-productivity periods and downtime periods from the operation plan of the load equipment LE and generates additional information that designates these periods as low-load periods TL. The additional information includes, for example, the start time (or the first unit load period) and end time (or the last unit load period) of the low-load periods TL. For example, as shown in Figure 10, when the load equipment LE starts operation, a warm-up is performed on the load equipment LE, and then processes such as production begin. In this case, the low-load periods TL will be from the end of the workday until the start time of the warm-up on the following day as specified in the operation plan.

[0103] <4-9> Auxiliary Operation Execution Module The auxiliary operation execution module 40, if the heat storage amount 73 falls below a predetermined value when the low-load period TL arrives, causes the first heat source device 21 to perform auxiliary operation during the low-load period TL. This restores the heat storage amount 73 in the water tank 23 during the low-load period TL when the actual heat demand of the load equipment LE falls below a predetermined value, and this heat storage amount 73 can be used to meet the excess demand at the start of operation of the load equipment LE. As a result, the load on the second heat source device 22 is reduced. The auxiliary operation execution module 40 sets the start time TS of the auxiliary operation based on the heat storage amount 73 of the water tank 23 calculated by the heat storage amount calculation module 38 and the additional information for the low-load period TL generated by the additional information generation module 39.

[0104] <4-9-1> Auxiliary operation When the auxiliary operation execution module 40 causes the first heat source device 21 to perform auxiliary operation, it determines the auxiliary operation period 75 of the first heat source device 21 based on the difference between the maximum heat storage capacity 74 of the water tank 23 and the amount of heat stored 73, and the heat supply capacity 72 of the first heat source device 21.

[0105] As shown in Figure 9, the auxiliary operation period 75 of the first heat source device 21 refers to the operating period (length of time) of the first heat source device 21 required until the heat storage amount 73 in the water tank 23 reaches the maximum heat storage capacity 74. The maximum heat storage capacity 74 of the water tank 23 is the amount of heat stored in the water (heat transfer medium HM) when the maximum amount that can be stored in the water tank 23 is reached. The maximum heat storage capacity 74 is a predetermined value determined by the capacity of the water tank 23 (full water setting) and the water temperature (or temperature setting). The difference between the maximum heat storage capacity 74 of the water tank 23 and the amount of heat stored 73 represents the amount of heat that can be additionally stored in the water tank 23 from the present time. Based on this, the auxiliary operation execution module 40 determines the auxiliary operation period [h] of the first heat source device 21 required to supply the additional heat, based on the amount of additional heat [J] that can be stored in the water tank 23 and the heat supply capacity per unit time [J / h] of the first heat source device 21.

[0106] Next, the auxiliary operation execution module 40 sets the auxiliary operation start time TS based on the comparison result of the length of the low-load period TL and the auxiliary operation period 75. Specifically, if the length of the low-load period TL is greater than or equal to the auxiliary operation period 75, the auxiliary operation execution module 40 sets the auxiliary operation start time TS to a time obtained by the auxiliary operation period 75 years prior to the end time of the low-load period TL. This applies, for example, to cases where sufficient time is secured until the end time of the low-load period TL, such as when the low-load period TL falls within a non-operating period. By doing so, the auxiliary operation of the first heat source device 21 can be started from the auxiliary operation start time TS, thereby maximizing the heat storage amount 73 in the water tank 23 when the load equipment LE starts operating. Figure 10 illustrates the case where the length of the low-load period TL is greater than or equal to the auxiliary operation period 75.

[0107] The auxiliary operation execution module 40 sets the start time TS of the low-load period TL as the start time TS of the auxiliary operation if the length of the low-load period TL is less than the auxiliary operation period 75. This applies, for example, to cases where sufficient time cannot be secured until the end time of the low-load period TL, such as when the low-load period TL falls within a low-productivity period. This allows the heat storage amount 73 in the water tank 23 to be restored to the required level even if it is not possible to maximize the heat storage amount 73 by the end time of the low-load period TL (process start time).

[0108] In this way, the auxiliary operation execution module 40 sets the auxiliary operation start time TS as shown in Figure 10. The auxiliary operation execution module 40 then sends an operation start command to the heat supply equipment 2 to cause the first heat source device 21 to perform auxiliary operation when the auxiliary operation start time TS arrives. The auxiliary operation execution module 40 transmits the auxiliary operation start time TS to the controller 61 via the communication network 8. The controller 61 activates the first heat source device 21 when the auxiliary operation start time TS arrives. As a result, the first heat source device 21 operates to increase the amount of heat stored in the water tank 23 in advance using the surplus heat supply capacity during the low-load period TL.

[0109] Furthermore, when performing auxiliary operation, if environmental conditions are in place to increase the hot water output temperature of the first heat source device 21 (for example, when the outside air temperature is high), the target hot water output temperature may be set higher than the normal temperature (for example, 70-90°C). This allows the heat storage capacity 73 to be restored to a higher level.

[0110] <4-9-2> Downward revision of planned values The planned value generation module 34 generates a planned value 52 that is revised downward according to the maximum heat storage capacity 74 if the excess period TE arrives immediately following the end of the low-load period TL.

[0111] As described above, the original planned value 52 is calculated by subtracting the heat supply capacity 72 of the first heat source device 21 from the virtual heat demand 71 (excess demand) during the excess time period TE. In contrast, the revised planned value 52 is calculated by subtracting the sum of the heat supply capacity 72 of the first heat source device 21 and the amount of heat stored in the water tank 23 after the auxiliary operation has finished 73 from the excess demand. In other words, since a portion of the heat demand exceeding the heat supply capacity 72 of the first heat source device 21 during the excess time period TE can be covered by the amount of heat stored 73 that has been pre-stored in the water tank 23 through auxiliary operation, the planned value generation module 34 generates a revised planned value 52 that reduces the amount of heat to be covered from the heat supply of the second heat source device 22.

[0112] For example, as shown in Figure 10, when the load equipment LE starts up, a lot of thermal energy is required to warm up the various production machinery and equipment. As a result, the actual heat demand exceeds the heat supply capacity 72 of the first heat source device 21, and the load on the second heat source device 22 also tends to become excessive. The planned value generation module 34 uses the amount of heat H1 generated by auxiliary operation (and the amount of heat originally remaining in the water tank 23) to cover a portion of the excess heat demand H2 that occurs during warm-up, and sets the remaining excess heat demand as the planned value 52 for the heat supply of the second heat source device 22. This reduces the heat supply of the second heat source device 22 by the amount of heat stored 73 in the water tank 23, even when a lot of thermal energy is required for warm-up at the start of operation. Since heat pumps are more energy efficient than boilers, replacing a portion of the heat H2 generated by the boiler with the heat H1 generated by the heat pump can contribute to energy saving of the heat supply equipment 2.

[0113] <4-10> UI Provisioning Module As shown in Figure 5, the UI provision module 41 provides a user interface (UI) for displaying information such as the operational performance of the driver assistance system 1 on the user terminal 45. The user interface is a means of accessing the driver assistance system 1. The user interface mainly includes a function to display the UI screen on the user terminal 45 and a function to receive operation input for various functions provided via the UI screen.

[0114] The UI module 41 displays various information on the user terminal 45, such as environmental information, operating information of the heat source equipment, operating conditions of the heat source equipment, operation plan of the load equipment LE, virtual heat demand, history of actual heat demand, planned value 52 of the second heat source equipment 22, and target hot water outlet temperature.

[0115] <4-11> Database Database 37 stores the operation plan of the load equipment LE, information on the load equipment LE, operating conditions of each heat source device, information on the water tank 23, various thresholds, and equipment flow diagrams that depict the overall or partial configuration of the heat supply equipment 2 and the factory 4.

[0116] [5] Example of a heat supply system configuration The configuration of the heat supply equipment 2 according to this embodiment for supplying the heat transfer medium HM to the load equipment LE can take various forms and is not particularly limited. A typical example of the configuration of the heat supply equipment 2 will be described below.

[0117] <5-1> First Configuration Example Figure 11 is a schematic diagram showing a first configuration example of the heat supply equipment 2 according to the embodiment. In Figure 11, the load equipment LE indirectly uses heated water (heat transfer medium HM) (i.e., provides thermal output). In Figure 11, the heating of the heat transfer medium HM by the first heat source device 21 takes place along the path through which the heat transfer medium HM is sent to the load equipment LE.

[0118] The heat supply equipment 2 includes a first heat source device 21 that heats the water using an electric heat pump, a second heat source device 22 that heats the water using a combustion or electric boiler, and a water tank 23. The water line 24 includes a distribution line 241 and a return line 242. The heat supply equipment 2 heats the water used by the load equipment LE within the business premises as a heat transfer medium HM.

[0119] The water tank 23 stores water, which is the heat transfer medium HM, as stored water. The water tank 23 is, for example, an open-type tank. The water tank 23 is equipped with a water level sensor 231 as an environmental sensor 5. When the water level sensor 231 detects a decrease in the water level in the water tank 23, replenishment water is supplied to the water tank 23 through the replenishment water line 243. The water tank 23 may also be equipped with other environmental sensors 5. In this case, the environmental sensor 5 is a temperature sensor that detects the temperature of the water stored in the water tank 23.

[0120] The water distribution line 241 and the water return line 242 connect the water tank 23 and the load equipment LE, respectively. In Figure 11, the water distribution line 241 and the water return line 242 form a circulation line for a hot water loop system. A water supply pump 244 is provided in the water distribution line 241. The water distribution line 241 is the supply pipe that supplies water from the water tank 23 to the load equipment LE. The water stored in the water tank 23 is supplied to the load equipment LE via the water distribution line 241. In the load equipment LE, heat is removed from the water through heat exchange, and the water temperature decreases. The water return line 242 is the return pipe that returns water from the load equipment LE to the water tank 23. The water that has been used in the load equipment LE and whose temperature has decreased flows to the water return line 242.

[0121] The first heat source device 21 is composed of an air-source heat pump. In the first configuration example shown in Figure 11, the first heat source device 21 further includes a sub-heat exchanger 216, a sub-circulation pump 217, and a sub-circulation line 218.

[0122] The sub-circulation line 218 connects the sub-heat exchanger 216 to the refrigerant condenser 212 (see Figure 2) of the first heat source device 21. Intermediate heat transfer medium HM2 flows through the sub-circulation line 218. The intermediate heat transfer medium HM2 circulating in the sub-circulation line 218 may be water. A sub-circulation pump 217 is provided in the sub-circulation line 218. The sub-circulation pump 217 circulates the heat transfer medium HM flowing through the sub-circulation line 218.

[0123] The first heat source device 21 absorbs heat from the air using a refrigerant evaporator 211. The first heat source device 21 then releases (heats) the absorbed heat to the intermediate heat transfer medium HM2 circulating in the sub-circulation line 218 using a refrigerant condenser 212. The first heat source device 21 also heats the water flowing through the return water line 242.

[0124] The sub-heat exchanger 216 performs heat exchange between the heat transfer medium HM flowing through the water supply line 24 and the intermediate heat transfer medium HM2 flowing through the sub-circulation line 218, thereby heating the heat transfer medium HM. In the first configuration example shown in Figure 11, the sub-heat exchanger 216 is located in the return water line 242 from the load equipment LE, and heats the water used as the heat transfer medium HM with the heat from the intermediate heat transfer medium HM2. The heated water is then sent to the water supply tank 23 via the return water line 242.

[0125] Environmental sensors 5 may be provided in the water supply line 24. The environmental sensors 5 are temperature sensors and may be provided in one or more locations in the water supply line 24. The installation locations of the environmental sensors 5 include, for example, the water distribution line 241 between the water supply tank 23 and the load equipment LE, the upstream location of the sub-heat exchanger 216 in the return water line 242, and the downstream location of the sub-heat exchanger 216 in the return water line 242. In Figure 11, the environmental sensors 5 are provided upstream of the location where the sub-heat exchanger 216 is located in the return water line 242. The upstream environmental sensors 5 are temperature sensors that detect the return temperature of the water. In Figure 11, the environmental sensors 5 are provided downstream of the location where the sub-heat exchanger 216 is located in the return water line 242. The downstream environmental sensors 5 are temperature sensors that detect the temperature of the water heated by the first heat source device 21 (hot water outlet temperature).

[0126] The second heat source device 22 heats the water in the water tank 23. The second heat source device 22 includes a group of steam boilers consisting of one or more steam boilers 221 (see Figure 2). The second heat source device 22 supplies steam to the steam line 25. The steam line 25 is equipped with a steam heater 251 and a steam supply valve 252.

[0127] The steam line 25 supplies steam ST from the steam boiler 221 to the steam heater 251. After heat exchange in the steam heater 251, the steam ST is discharged from the steam heater 251 through the steam line 25. The steam heater 251 is installed inside the water tank 23. The steam heater 251 performs heat exchange between the water in the water tank 23 and the steam ST flowing through the steam line 25, heating the stored water. The steam feed valve 252 controls the flow state of the steam ST flowing through the steam line 25. Preferably, the steam feed valve 252 is a proportional control valve with an adjustable opening.

[0128] Thus, in the first configuration example, the first heat source device 21 heats the water via a sub-heat exchanger 216 located in the return water line 242. The second heat source device 22 heats the water via a steam heater 251 located in the water tank 23.

[0129] The configuration of the first heat source device 21 may also be such that the return water line 242 is directly connected to the refrigerant condenser 212. In this case, the first heat source device 21 dissipates heat (heats the water) from the refrigerant circulating in the refrigerant circulation line 215 to the heat transfer medium HM (water) circulating in the return water line 242 via the refrigerant condenser 212. In this case, the sub-heat exchanger 216, sub-circulation pump 217, and sub-circulation line 218 can be omitted.

[0130] <5-2> Second Configuration Example Figure 12 is a schematic diagram showing a second configuration example of the heat supply equipment 2 according to the embodiment. In Figure 12, the load equipment LE indirectly uses heated water (heat transfer medium HM) (i.e., provides thermal output). In Figure 12, the heating of the heat transfer medium HM by the first heat source device 21 is performed outside the path through which the heat transfer medium HM is sent to the load equipment LE, which is different from the first configuration example. Note that in the second configuration example, explanations of configurations similar to those in the first configuration example may be omitted.

[0131] As shown in Figure 12, the first heat source device 21 is not located in the return water line 242 of the heat supply equipment 2 in the second configuration example. The heat supply equipment 2 of the embodiment includes a circulation line 245 that circulates the water stored in the water tank 23. In the second configuration example, the first heat source device 21 heats the water flowing through the circulation line 245 that circulates the water stored in the water tank 23. The second heat source device 22 heats the water stored in the water tank 23.

[0132] The circulation line 245 is connected at one end to the water tank 23 and is a line for circulating the water in the water tank 23. A sub-heat exchanger 216 is located in the circulation line 245. A circulation pump 26 is provided in the circulation line 245.

[0133] The sub-heat exchanger 216 performs heat exchange between the water flowing through the circulation line 245 and the intermediate heat transfer medium HM2 flowing through the sub-circulation line 218. The first heat source device 21 heats the water (heat transfer medium HM) flowing through the circulation line 245 with the temperature of the intermediate heat transfer medium HM2.

[0134] Environmental sensors 5 are provided in the return water line 242 and the circulation line 245. These environmental sensors 5 are temperature sensors that detect the temperature of the water (heat transfer medium HM).

[0135] As described above, in the second configuration example, the first heat source device 21 heats the water via a sub-heat exchanger 216 located in the circulation line 245. The circulation pump 26 sends the heated water from the circulation line 245 into the water tank 23, and sends the stored water in the water tank 23 to the sub-heat exchanger 216 in the circulation line 245. The water stored in the water tank 23 is heated by the circulation of the water.

[0136] <5-3> Third Configuration Example Figure 13 is a schematic diagram showing a third configuration example of the heat supply equipment 2 according to the embodiment. In Figure 13, the load equipment LE directly uses heated water (i.e., hot water output). In Figure 13, heating of the heat transfer medium HM by the first heat source device 21 takes place on the path through which the heat transfer medium HM is sent to the load equipment LE. Note that in the third configuration example, explanations of configurations similar to those in the first configuration example may be omitted.

[0137] In the first and second configuration examples, a return water line 242 is provided to return water from the load equipment LE to the water tank 23. However, in the heat supply equipment 2 according to the third configuration example, the return water line 242 is not provided. In other words, in this third configuration example, the load equipment LE directly uses the heated water as, for example, washing water (i.e., hot water output). Since the water is consumed in the load equipment LE, it is not returned to the water tank 23.

[0138] As shown in Figure 13, in the heat supply equipment 2 according to the third configuration example, the water supply line 246 is connected to the water tank 23. A water supply pump 27 is installed in the water supply line 246.

[0139] The first heat source device 21 heats the water (heat transfer medium HM) flowing through the water supply line 246. That is, the sub-heat exchanger 216 of the first heat source device 21 is located in the water supply line 246. The second heat source device 22 heats the water in the water supply tank 23. Here, the configuration in which the first heat source device 21 heats the water flowing through the water supply line 246 and the configuration in which the second heat source device 22 heats the water in the hot water tank are the same as in the first configuration example described above, so no explanation is given.

[0140] <5-4> Fourth Configuration Example Figure 14 is a schematic diagram showing a fourth configuration example of the heat supply equipment 2 according to the embodiment. In Figure 14, the load equipment LE directly uses heated water (i.e., hot water output). In Figure 14, heating of the heat transfer medium HM by the first heat source device 21 is performed outside the path through which the heat transfer medium HM is sent to the load equipment LE. Note that in the fourth configuration example, the explanation of configurations similar to those in the second configuration example may be omitted.

[0141] In the fourth configuration example, similar to the third configuration example, the load equipment LE directly uses the heated water (i.e., hot water output). On the other hand, in the fourth configuration example, similar to the second configuration example, the first heat source device 21 heats the water in the circulation line 245 that circulates the water stored in the water tank 23. Note that in the fourth configuration example, explanations of configurations similar to those in the second configuration example may be omitted.

[0142] As shown in Figure 14, the sub-heat exchanger 216 of the first heat source device 21 is not located in the water supply line 246 of the heat supply equipment 2 of the embodiment. In the fourth configuration example, the first heat source device 21 heats the water flowing through the circulation line 245. That is, the sub-heat exchanger 216 of the first heat source device 21 is located in the circulation line 245. The second heat source device 22 heats the water stored in the water tank 23. Here, the configuration in which the first heat source device 21 heats the water (heat transfer medium HM) flowing through the circulation line 245 and the configuration in which the second heat source device 22 heats the water in the hot water tank are the same as in the second configuration example, so an explanation is omitted.

[0143] [6] Driving assistance methods and driving assistance application programs Figure 15 is a flowchart illustrating a driving assistance method according to an embodiment. Figure 15 is both a processing flowchart that the driving assistance application program 100 according to the embodiment causes the computer 10 to execute, and an operation flowchart of the driving assistance system 1 according to the embodiment.

[0144] The operation support method according to this embodiment is an operation support method for a heat supply facility 2 which includes a first heat source device 21 that is operated as a base load device in response to heat demand, and a second heat source device 22 that is operated as a peak load device in response to heat demand.

[0145] As shown in Figure 15, the operation support method according to the embodiment includes the computer 10 generating prediction information 50 of the virtual heat demand 71 for each unit load time period on the day of operation using a heat demand change pattern model or a trained inference model (i.e., prediction model 70) stored in the computer 10 (step S10). The operation support application program 100 causes the computer 10 to operate as a prediction information generation module 32 and executes the process of generating prediction information 50 of the virtual heat demand 71 for each unit load time period.

[0146] The operation support method according to the embodiment includes the computer 10 generating estimated information 51 of the excess time period TE in which the virtual heat demand 71 exceeds the heat supply capacity 72 of the first heat source device 21, based on the predicted information 50 (step S11). The operation support application program 100 causes the computer 10 to operate as an estimated information generation module 33 and execute the process of generating estimated information 51 of the excess time period TE.

[0147] The operation support method according to the embodiment includes the computer 10 generating a planned value 52 for the amount of heat supplied by the second heat source device 22 necessary to satisfy the virtual heat demand amount 71 during the excess time period TE, based on estimated information 51 (step S12). The operation support application program 100 causes the computer 10 to operate as a planned value generation module 34 and execute the process of generating the planned value 52 for the amount of heat supplied by the second heat source device 22.

[0148] The operation support method according to the embodiment includes sending a planned value 52 to the heat supply equipment 2 via the communication network 8 using the computer 10, and causing the second heat source device 22 to perform heating operation according to the planned value 52 when the excess time period TE arrives (step S13). The operation support application program 100 causes the computer 10 to operate as a planned value transmission module 35, thereby sending the planned value 52 to the controller 61 of the heat supply equipment 2 via the communication network 8. As a result, the controller 61 controls the heating operation of the second heat source device 22 according to the planned value 52. This eliminates the heat supply shortage of the peak load machine (second heat source device 22) in response to the increase in heat demand. Furthermore, since there is no need to keep the peak load machine in a hot standby state, no energy loss occurs.

[0149] Figure 16 is a flowchart showing the process related to auxiliary operation. As shown in Figure 16, the operation support method according to the embodiment includes the computer 10 calculating the amount of heat stored in the water tank 23 based on information from the environmental sensor 5 installed in the heat supply equipment 2 (step S20). The operation support application program 100 causes the computer 10 to operate as a heat storage amount calculation module 38 and executes the process of calculating the amount of heat stored in the water tank 23.

[0150] The operation support method according to the embodiment includes the computer 10 generating additional information for low-load time periods TL, in which the actual heat demand is below a predetermined value, based on the operation plan of the load equipment LE (step S21). The operation support application program 100 causes the computer 10 to operate as an additional information generation module 39 and execute the process of generating additional information for low-load time periods TL.

[0151] The operation support method according to this embodiment includes, if the amount of heat stored falls below a predetermined value when the low-load period TL arrives, the computer 10 causes the first heat source device 21 to perform auxiliary operation during the low-load period TL. The operation support application program 100 causes the computer 10 to operate as an auxiliary operation execution module 40, thereby causing the first heat source device 21 to perform auxiliary operation.

[0152] Specifically, the auxiliary operation execution module 40 compares the amount of heat stored in the water during the low-load period TL with a predetermined value. If the amount of heat stored falls below the predetermined value when the low-load period TL arrives (step S22; YES), the auxiliary operation execution module 40 causes the first heat source device 21 to perform auxiliary operation (step S23). Specifically, the auxiliary operation execution module 40 determines the auxiliary operation period 75 for the first heat source device 21, sets the start time TS for the auxiliary operation, and sends an operation start command to the heat supply equipment 2 so that the first heat source device 21 performs auxiliary operation when the start time TS arrives.

[0153] On the other hand, if the amount of stored heat does not fall below a predetermined value when the low-load period TL arrives (step S22; NO), the auxiliary operation execution module 40 does not cause the first heat source device 21 to perform auxiliary operation.

[0154] If the excess time period TE arrives immediately following the end of the low-load time period TL, the driver assistance application program 100 causes the computer 10 to operate as a planned value generation module 34 to generate a planned value 52 that has been revised downward according to the maximum heat storage capacity 74.

[0155] In other words, the planned value generation module 34 compares the end time of the low-load period TL with the start time of the excess period TE in the forecast information 50. If the excess period TE arrives immediately following the end time of the low-load period TL (step S24; YES), the planned value generation module 34 generates a planned value 52 that has been revised downward according to the maximum heat storage capacity 74 of the water tank 23. If the planned value generation module 34 has generated a planned value 52 in step S12 of Figure 15, it updates it with the new, revised planned value 52. This reduces the load on the second heat source device 22 when the excess period TE arrives by pre-recovering the heat storage amount 73 using the surplus heat supply capacity 72 of the first heat source device 21 during the low-load period TL.

[0156] On the other hand, if the excess time period TE does not occur immediately following the end of the low-load time period TL (step S24; NO), the plan value generation module 34 does not generate a downwardly revised plan value 52. In this case, the plan value 52 generated in step S12 of Figure 15 is transmitted to the controller 61 of the heat supply equipment 2.

[0157] [7] Effects As described above, in the embodiment, the operation support application program 100 is an operation support application program 100 that operates on a computer 10 capable of sending and receiving information via a communication network 8 with a heat supply facility 2 which includes a first heat source device 21 that operates as a base load machine in response to heat demand and a second heat source device 22 that operates as a peak load machine in response to heat demand, and uses a heat demand change pattern model or a trained inference model (prediction model 70) stored in the computer 10 to predict information 50 of the virtual heat demand amount 71 for each unit load time period on the day of operation. The functions of the prediction information generation module 32 are to generate (prediction information generation module 32), generate prediction information 51 of the excess time period TE in which the virtual heat demand 71 exceeds the heat supply capacity 72 of the first heat source device 21 based on the prediction information 50 (prediction information generation module 33), generate a planned value 52 of the amount of heat supplied by the second heat source device 22 necessary to satisfy the virtual heat demand 71 in the excess time period TE based on the prediction information 51 (planned value generation module 34), and transmit the planned value 52 to the heat supply equipment 2 so that when the excess time period TE arrives, the second heat source device 22 will be heated according to the planned value 52 (planned value transmission module 35).

[0158] According to this configuration, the prediction information 50 generates estimated information 51 for the excess time period TE, in which the heat supply capacity 72 of the first heat source device 21 cannot keep up with the virtual heat demand 71, and the second heat source device 22 needs to be started. From the estimated information 51, a planned value 52 for the amount of heat supplied by the second heat source device 22 is generated to satisfy the virtual heat demand 71 during the excess time period TE. This planned value 52 can be calculated by subtracting the heat supply capacity 72 of the first heat source device 21 from the virtual heat demand 71 (i.e., excess demand) during the excess time period TE. When the excess time period TE arrives, the second heat source device 22 is operated under operating conditions corresponding to the planned value 52 for the amount of heat supplied. In this way, the time change of the virtual heat demand 71 on the day of operation can be predicted, and the amount of heat supplied by the second heat source device 22 can be planned after narrowing down the excess time period TE. By operating the heating system according to the planned value of 52, the heat supply shortage from the peak load unit (second heat source unit 22) to meet the increased heat demand can be resolved. Furthermore, since there is no need to keep the peak load unit in a hot standby state, no energy loss occurs.

[0159] In this embodiment, the first heat source device 21 has a heat pump for heating the water, and the second heat source device 22 has a group of steam boilers for heating the water with steam ST. The planned value 52 includes the specific enthalpy and mass of the steam ST generated by the group of steam boilers. In this configuration, the amount of heat supplied (energy) from the group of steam boilers required during the excess time period TE is the specific enthalpy of the steam (total heat, unit: J / kg) multiplied by the mass of the steam (unit: kg). Since the specific enthalpy changes with the pressure of saturated steam, the amount of heat supplied can be adjusted according to the planned value 52 by manipulating the operating pressure and evaporation rate of the steam boiler 221.

[0160] In this embodiment, the planned value 52 includes the number of operating steam boilers in the steam boiler group and the combustion rate for each individual steam boiler. In this configuration, the operating pressure of each steam boiler 221 can be set individually. The evaporation rate of each steam boiler 221 can be controlled by increasing or decreasing the number of operating steam boilers in the steam boiler group and adjusting the combustion rate for each individual steam boiler 221. This allows the operation of the second heat source device 22, which has a steam boiler group, to be appropriately controlled in accordance with the planned value 52.

[0161] In this embodiment, the heat supply equipment 2 includes a water tank 23 for storing water heated by the first heat source device 21 and the second heat source device 22. The operation support application program 100 further causes the computer 10 to calculate the amount of heat stored in the water stored in the water tank 23 based on information from the environmental sensor 5 installed in the heat supply equipment 2 (function of the heat storage amount calculation module 38), to generate additional information for the low-load period TL when the actual heat demand is below a predetermined value based on the operation plan of the load equipment LE (function of the additional information generation module 39), and, if the amount of heat stored 73 is below a predetermined value when the low-load period TL arrives, to cause the first heat source device 21 to perform auxiliary operation during the low-load period TL (function of the auxiliary operation execution module 40). Here, when the load equipment LE starts up, a lot of thermal energy is required for warming up, so the actual heat demand exceeds the heat supply capacity 72 of the first heat source device 21, and the load on the second heat source device 22 also tends to be large. In this configuration, the computer 10 generates additional information on low-load periods TL, such as low-productivity periods and downtime periods, from the operation plan of the load equipment LE. If the amount of heat stored in the water tank 23 decreases when a low-load period TL arrives, as determined from the additional information, the computer 10 causes the first heat source device 21 to perform auxiliary operation during the low-load period TL. This restores the amount of heat stored in the water tank 23 73 during the low-load period TL when the actual heat demand of the load equipment LE falls below a predetermined value, and this stored heat 73 can be used to meet the heat demand during the excess period TE. As a result, the amount of heat supplied by the second heat source device 22 during the excess period TE is reduced.

[0162] In this embodiment, when the operation support application program 100 causes the first heat source device 21 to perform auxiliary operation, it further causes the computer 10 (auxiliary operation execution module 40) to determine the auxiliary operation period 75 of the first heat source device 21 based on the difference between the maximum heat storage capacity 74 of the water tank 23 and the amount of stored heat 73, and the heat supply capacity 72 of the first heat source device 21; to set the start time TS of the auxiliary operation based on the comparison result of the length of the low-load period TL and the auxiliary operation period 75; and to send an operation start command to the heat supply equipment 2 so that the first heat source device 21 performs auxiliary operation when the start time TS arrives. In this configuration, the computer 10 determines the auxiliary operation period [h] of the first heat source device 21 required to supply additional heat based on the amount of additional heat [J] that can be stored in the water tank 23 and the heat supply capacity [J / h] of the first heat source device 21. If the length of the low-load period TL is greater than or equal to the auxiliary operation period 75, the computer 10 sets a specified time TS, which is, for example, the auxiliary operation start time, which is the auxiliary operation period 75 years prior to the end time of the low-load period TL, and causes the first heat source device 21 to perform auxiliary operation when the start time TS arrives. This makes it possible to maximize the amount of heat stored 73 in the water tank 23 by the time the excess period TE arrives. Alternatively, if the length of the low-load period TL is less than the auxiliary operation period 75, the start time TS of the low-load period TL is set as the start time TS of the auxiliary operation. This makes it possible to restore the amount of heat stored 73 in the water tank 23 to the required level even if it is not possible to maximize it by the time the excess period TE arrives.

[0163] In this embodiment, if the excess period TE arrives immediately following the end of the low-load period TL, the operation support application program 100 causes the computer 10 (planned value generation module 34) to generate a planned value 52 that has been revised downward according to the maximum heat storage capacity 74. In this configuration, if the excess period TE begins at the end of the low-load period TL, the computer 10 generates a revised planned value 52 (heat supply amount of the second heat source device 22). The planned value 52 before revision is, for example, obtained by subtracting the heat supply capacity 72 of the first heat source device 21 from the virtual heat demand amount 71 (excess demand amount) of the excess period TE. The revised planned value 52 can be obtained by subtracting the heat supply capacity 72 of the first heat source device 21 and the maximum heat storage capacity 74 of the water tank 23 from the excess demand amount. As a result, even when a large amount of thermal energy is required during the excess time period TE, the amount of heat supplied by the second heat source device 22 is reduced by the amount of the maximum heat storage capacity 74 of the water tank 23. Since the heat pump is more energy efficient than the boiler, it can contribute to energy saving of the heat supply equipment 2 by replacing a portion of the heat generated by the boiler with the heat generated by the heat pump.

[0164] In this embodiment, the heat supply equipment 2 includes a sensor group consisting of one or more environmental sensors 5 arranged in the heat supply equipment 2, and a controller 61 that controls the operation of the first heat source device 21 and the second heat source device 22. The computer 10 is configured to acquire environmental information detected by the sensor group and operational information generated by the controller 61 via a communication network 8, and has an information storage platform 36 that stores the acquired environmental information and operational information. The change pattern model or trained inference model (predictive model 70) is generated by utilizing the environmental information stored in the information storage platform 36. In this configuration, by storing environmental information and operational information within the factory 4 where thermal energy is supplied and demanded in the information storage platform 36, it becomes possible to generate historical information of actual hourly thermal demand corresponding to a predetermined season and predetermined day of the week from the stored environmental information. From the historical information, a change pattern model of thermal demand can be generated by statistical processing, and a trained inference model can be generated by machine learning. As a result, the obtained change pattern model and trained inference model can be used to appropriately predict the virtual heat demand 71 on the day of operation, reflecting past changes in actual heat demand.

[0165] In this embodiment, the operation support system 1 is an operation support system 1 for a heat supply facility 2 comprising a first heat source device 21 operated as a base load machine to meet heat demand, and a second heat source device 22 operated as a peak load machine to meet heat demand, and comprises a sensor group consisting of one or more environmental sensors 5 arranged in the heat supply facility 2, a controller 61 that controls the operation of the first heat source device 21 and the second heat source device 22, a communication network 8 for transmitting information, and an information processing device 6 configured to acquire environmental information detected by the sensor group and operational information generated by the controller 61 via the communication network 8, wherein the information processing device 6 comprises an information storage platform 36 for storing acquired environmental information and operational information, and utilizes the environmental information stored in the information storage platform 36 The system includes: a prediction information generation module 32 that generates prediction information 50 of virtual heat demand 71 for each unit load time period on the day of operation using a heat demand change pattern model or a trained inference model (prediction model 70) generated by utilizing the above; an inference information generation module 33 that generates prediction information 51 of excess time period TE when the virtual heat demand 71 exceeds the heat supply capacity 72 of the first heat source device 21 based on the prediction information 50; a plan value generation module 34 that generates a plan value 52 of the amount of heat supplied by the second heat source device 22 necessary to satisfy the virtual heat demand 71 in excess time period TE based on the inference information 51; and a plan value transmission module 35 that transmits the plan value 52 to the controller 61 via the communication network 8 and causes the second heat source device 22 to perform heating operation according to the plan value 52 when the excess time period TE arrives.

[0166] According to this configuration, the prediction information 50 generates estimated information 51 for the excess time period TE, in which the heat supply capacity 72 of the first heat source device 21 cannot keep up with the virtual heat demand 71, and the second heat source device 22 needs to be started. From the estimated information 51, a planned value 52 for the amount of heat supplied by the second heat source device 22 is generated to satisfy the virtual heat demand 71 during the excess time period TE. This planned value 52 is obtained by subtracting the heat supply capacity 72 of the first heat source device 21 from the virtual heat demand 71 (i.e., excess demand) during the excess time period TE. When the excess time period TE arrives, the second heat source device 22 is operated under operating conditions corresponding to the planned value 52 for the amount of heat supplied. In this way, the time change of the virtual heat demand 71 on the day of operation can be predicted, the excess time period TE can be narrowed down, and the amount of heat supplied by the second heat source device 22 can be planned. By operating the heating system according to the planned value of 52, the heat supply shortage from the peak load unit (second heat source unit 22) to meet the increased heat demand can be resolved. Furthermore, since there is no need to keep the peak load unit in a hot standby state, no energy loss occurs.

[0167] In one embodiment, the operation support method is an operation support method for a heat supply facility 2 comprising a first heat source device 21 operated as a base load device in response to heat demand and a second heat source device 22 operated as a peak load device in response to heat demand, and includes: generating prediction information 50 of virtual heat demand 71 for each unit load time period on the day of operation using a heat demand change pattern model or a trained inference model (prediction model 70) stored in a computer 10; generating estimation information 51 of the excess time period TE in which the virtual heat demand 71 exceeds the heat supply capacity 72 of the first heat source device 21 based on the prediction information 50; generating a planned value 52 of the amount of heat supplied by the second heat source device 22 necessary to satisfy the virtual heat demand 71 in the excess time period TE based on the estimation information 51; and transmitting the planned value 52 to the heat supply facility 2 via a communication network 8, causing the second heat source device 22 to perform heating operation according to the planned value 52 when the excess time period TE arrives.

[0168] According to this configuration, the prediction information 50 generates estimated information 51 for the excess time period TE, in which the heat supply capacity 72 of the first heat source device 21 cannot keep up with the virtual heat demand 71, and the second heat source device 22 needs to be started. From the estimated information 51, a planned value 52 for the amount of heat supplied by the second heat source device 22 is generated to satisfy the virtual heat demand 71 during the excess time period TE. This planned value 52 is obtained by subtracting the heat supply capacity 72 of the first heat source device 21 from the virtual heat demand 71 (i.e., excess demand) during the excess time period TE. When the excess time period TE arrives, the second heat source device 22 is operated under operating conditions corresponding to the planned value 52 for the amount of heat supplied. In this way, the time change of the virtual heat demand 71 on the day of operation can be predicted, the excess time period TE can be narrowed down, and the amount of heat supplied by the second heat source device 22 can be planned. By operating the heating system according to the planned value of 52, the heat supply shortage from the peak load unit (second heat source unit 22) to meet the increased heat demand can be resolved. Furthermore, since there is no need to keep the peak load unit in a hot standby state, no energy loss occurs.

[0169] [8] Contribution to the United Nations-led Sustainable Development Goals (SDGs) The operational support system described in this disclosure uses a relatively energy-efficient heat pump as the base load unit for heat demand and a relatively energy-inefficient boiler as the peak load unit for heat demand. The peak load unit is then operated to prevent energy loss when excess heat demand occurs. This improves the energy efficiency and productivity of the entire business facility, including the factory, and can contribute to achieving Sustainable Development Goal 7, "Affordable and Clean Energy." Furthermore, the improvement in energy efficiency can also reduce carbon dioxide emissions, contributing to achieving Goal 13, "Take urgent action to combat climate change." [Explanation of symbols]

[0170] 1... Driving support system, 2... Heat supply equipment, 3... Business office, 3A... 1st business office, 3B... 2nd business office, 3C... 3rd business office, 4... Factory, 4A... 1st factory, 4B... 2nd factory, 5... Environmental sensor, 6... Information processing device, 7... Data acquisition terminal, 8... Communication network, 10... Computer, 11... Processor, 12... Memory device, 13... Communication interface, 14... Input / output interface, 21... 1st heat source device, 22... 2nd heat source device, 23... Water tank, 24... Water line, 2 5…Steam line, 31…Information processing module, 32…Predictive information generation module, 33…Estimated information generation module, 34…Planned value generation module, 35…Planned value transmission module, 36…Information storage platform, 37…Database, 38…Heat storage amount calculation module, 39…Additional information generation module, 40…Auxiliary operation execution module, 41…UI provision module, 45…User terminal, 50…Predictive information, 51…Estimated information, 52…Planned value, 61…Controller, 61A…Microcomputer, 61B…Programmable logic controller, 62…Edge computer, 63…Gateway, 64…Guest computer, 65…Host computer, 70…Predictive model, 71…Virtual heat demand, 72…Heat supply capacity, 73…Heat storage amount, 74…Maximum heat storage capacity, 75…Auxiliary operation period, 100…Operation support application program, 211…Refrigerant evaporator, 212…Refrigerant condenser, 213…Refrigerant compressor, 214…Expansion valve, 215… Refrigerant circulation line, 216... Sub-heat exchanger, 217... Sub-circulation pump, 218... Sub-circulation line, 221... Steam boiler, 231... Water level sensor, 241... Water distribution line, 242... Return water line, 243... Makeup water line, 244... Water supply pump, 245... Circulation line, 246... Feedwater line, 251... Steam heater, 252... Steam supply valve, HM... Heat transfer medium, HM2... Intermediate heat transfer medium, LE... Load equipment, ST... Steam, TL... Low load period, TE... Overload period, TS... Start time of auxiliary operation.

Claims

1. An operation support application program that operates on a computer capable of sending and receiving information via a communication network with a heat supply system comprising a first heat source unit operated as a base load unit to meet heat demand, and a second heat source unit operated as a peak load unit to meet heat demand, To the aforementioned computer, Using the heat demand change pattern model or trained inference model stored in the aforementioned computer, predictive information on virtual heat demand for each unit load time period on the day of operation is generated. Based on the aforementioned prediction information, estimated information is generated regarding the excess time period in which the virtual heat demand exceeds the heat supply capacity of the first heat source device. Based on the estimated information, a planned value for the amount of heat supplied by the second heat source device is generated to satisfy the virtual heat demand during the excess time period. The planned value is transmitted to the heat supply equipment, and when the excess time period arrives, the heating operation of the second heat source device is performed according to the planned value, and the following is performed: A driver assistance application program.

2. The first heat source device has a heat pump for heating the water, The second heat source device has a group of steam boilers that heat the water with steam, The aforementioned planned values ​​include the specific enthalpy and mass of the steam generated by the steam boiler group. The driver assistance application program according to claim 1.

3. The aforementioned planned values ​​include the number of operating steam boilers in the group and the combustion rate for each individual steam boiler. The driver assistance application program according to claim 2.

4. The heat supply equipment includes a water tank for storing water heated by the first heat source device and the second heat source device, To the aforementioned computer, Based on information from environmental sensors installed in the heat supply equipment, the amount of heat stored in the water tank is calculated. Based on the operating plan of the load equipment, additional information is generated for low-load periods when the actual heat demand falls below a predetermined value. If the amount of heat stored falls below a predetermined value when the low-load period arrives, the first heat source device is to perform auxiliary operation during the low-load period, and the following actions are to be performed: A driver assistance application program according to any one of claims 1 to 3.

5. When the first heat source device is to perform the auxiliary operation, To the aforementioned computer, The auxiliary operation period of the first heat source device is determined based on the difference between the maximum heat storage capacity of the water tank set in advance and the amount of heat stored, and the heat supply capacity of the first heat source device. Based on the comparison result between the length of the low-load period and the auxiliary operation period, the start time of the auxiliary operation is set. To send an operation start command to the heat supply equipment so that the first heat source device performs the auxiliary operation when the aforementioned start time arrives, and to further cause the equipment to perform the following: The driver assistance application program according to claim 4.

6. If the aforementioned overload period begins immediately following the end of the aforementioned low-load period, The computer is instructed to generate the planned value which has been revised downward according to the maximum heat storage capacity. The driver assistance application program according to claim 5.

7. The aforementioned heat supply equipment is A sensor group consisting of one or more environmental sensors arranged in the heat supply equipment, The system includes a controller that controls the operation of the first heat source device and the second heat source device, The computer is configured to acquire environmental information detected by the sensor group and operational information generated by the controller via the communication network, and has an information storage platform for storing the acquired environmental information and operational information. The aforementioned change pattern model or the aforementioned trained inference model is generated by utilizing the environmental information stored in the information storage platform. The driver assistance application program according to claim 1.

8. An operation support system for a heat supply facility comprising a first heat source unit operated as a base load unit to meet heat demand, and a second heat source unit operated as a peak load unit to meet heat demand, A sensor group consisting of one or more environmental sensors arranged in the heat supply equipment, A controller that controls the operation of the first heat source device and the second heat source device, A communication network that transmits information, The system includes an information processing device configured to acquire environmental information detected by the sensor group and operational information generated by the controller via the communication network, The aforementioned information processing device is An information storage platform for storing the acquired environmental information and operational information, A prediction information generation module that generates prediction information for virtual heat demand for each unit load time period on the day of operation, using a heat demand change pattern model or a trained inference model generated by utilizing the environmental information stored in the information storage platform, Based on the aforementioned prediction information, an estimation information generation module generates estimation information for the excess time period in which the virtual heat demand exceeds the heat supply capacity of the first heat source device, A planning value generation module that generates a planned value for the amount of heat supplied by the second heat source device necessary to satisfy the virtual heat demand during the excess period based on the estimated information, The system includes a planned value transmission module that transmits the planned value to the controller via the communication network and causes the second heat source device to perform heating operation according to the planned value when the excess time period arrives. Driver assistance system.

9. A method for supporting the operation of a heat supply system comprising a first heat source system operated as a base load system to meet heat demand, and a second heat source system operated as a peak load system to meet heat demand, Using a heat demand change pattern model or a trained inference model stored in a computer, predictive information on virtual heat demand for each unit load time period on the day of operation is generated. Based on the aforementioned prediction information, estimated information is generated regarding the excess time period in which the virtual heat demand exceeds the heat supply capacity of the first heat source device. Based on the estimated information, a planned value for the amount of heat supplied by the second heat source device is generated to satisfy the virtual heat demand during the excess time period. This includes transmitting the planned value to the heat supply equipment via a communication network, and causing the second heat source device to perform heating operation according to the planned value when the excess time period arrives. Driving assistance methods.

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