JP2023150320A - Facility management system, facility management method, and facility management program - Google Patents

Abstract

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

Description

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

Conventionally, systems for managing energy consumption of facilities are known. For example, a system is known that optimizes energy consumption by estimating setting values of equipment installed in facilities such as buildings based on various data (see, for example, Patent Document 1).

International Publication No. 2012/118067

By the way, in facilities, it is possible to manage equipment using a communication standard for constructing a building network, such as BACnet (Building Automation and Control Networking Protocol) (“BACnet”; registered trademark). The data acquired using BACnet includes not only equipment measurement data but also detection data (environmental data, etc.) from various sensors installed in the facility. With conventional technology, it is difficult to configure settings for optimizing energy consumption of equipment within a facility using various data related to the facility.

An object of the present invention is to provide a facility management system, a facility management method, and a facility management program that can optimize the energy consumption of a facility using various data regarding the facility.

A facility management system according to one aspect of the present invention includes an acquisition processing unit that acquires facility data including measurement data of equipment in a facility and environmental data corresponding to the facility, and the facility acquired by the acquisition processing unit. an identification processing unit that identifies whether each of the data is data whose output value can be adjusted or data whose output value cannot be adjusted; and adjustable first facility data corresponding to the first equipment; and an estimation processing unit that estimates an optimal setting value of the first facility data based on non-adjustable second facility data related to the first facility data.

A facility management method according to another aspect of the present invention includes an acquisition step in which one or more processors acquire facility data including measurement data of equipment in the facility and environmental data corresponding to the facility; an identification step of identifying whether each of the obtained facility data is data whose output value is adjustable or data whose output value is not adjustable; The present invention is a facility management method that executes an estimation step of estimating an optimal setting value of the first facility data based on facility data and non-adjustable second facility data related to the first facility data.

A facility management program according to another aspect of the present invention includes an acquisition step of acquiring facility data including measurement data of equipment in the facility and environmental data corresponding to the facility; for each, an identification step of identifying whether the output value is adjustable data or the output value is non-adjustable data; first adjustable facility data corresponding to the first equipment; and the first adjustable facility data. A facility management program for causing one or more processors to execute an estimating step of estimating an optimal setting value of the first facility data based on non-adjustable second facility data related to the facility data. .

According to the present invention, it is possible to provide a facility management system, a facility management method, and a facility management program that can optimize the energy consumption of a facility using various data related to the facility.

FIG. 1 is a block diagram showing the configuration of a facility management system according to an embodiment of the present invention. FIG. 2 is a diagram showing an example of a monitoring equipment information DB used in the facility management system according to the embodiment of the present invention. FIG. 3 is a diagram showing an example of a facility data information DB used in the facility management system according to the embodiment of the present invention. FIG. 4 is a diagram showing an example of data names included in the facility data information DB according to the embodiment of the present invention. FIG. 5 is a diagram showing an example of the adjustment availability information DB used in the facility management system according to the embodiment of the present invention. FIG. 6 is a diagram illustrating an example of identification processing in the management server according to the embodiment of the present invention. FIG. 7 is a diagram illustrating an example of identification processing in the management server according to the embodiment of the present invention. FIG. 8 is a diagram illustrating an example of estimation processing in the management server according to the embodiment of the present invention. FIG. 9 is a diagram showing an example of a recommended setting page displayed on the administrator terminal according to the embodiment of the present invention. FIG. 10 is a diagram showing an example of a recommended setting page displayed on the administrator terminal according to the embodiment of the present invention. FIG. 11 is a flowchart illustrating an example of the procedure of facility management processing executed by the facility management system according to the embodiment of the present invention. FIG. 12 is a flowchart illustrating an example of the procedure of facility management processing executed by the facility management system according to the embodiment of the present invention.

Embodiments of the present invention will be described below with reference to the accompanying drawings to provide an understanding of the present invention. Note that the following embodiments are examples of embodying the present invention, and do not limit the technical scope of the present invention.

[Facility management system 1]
As shown in FIG. 1, a facility management system 1 according to an embodiment of the present invention includes a management server 2, a monitoring device 3, and an administrator terminal 4. The management server 2, the monitoring device 3, and the administrator terminal 4 can communicate via a communication network NW such as the Internet, LAN, WAN, or public telephone line. The facility management system 1 is introduced into a facility where a plurality of facilities are installed. The facilities include various facilities such as commercial facilities such as commercial buildings, public facilities such as government offices, accommodation facilities such as hotels and inns, and complex facilities. The equipment includes various equipment such as air conditioning equipment, boilers, refrigerators, pumps, and blowers, electrical equipment such as high-voltage equipment, generators, and power supply equipment, and firefighting equipment such as alarms and fire extinguishers. In this embodiment, a commercial building is cited as an example of the facility.

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

The management server 2 provides equipment management services to each facility and operates an equipment management service site. Specifically, the management server 2 acquires the monitoring results (measurement data, environmental data, etc.) of the monitored equipment by the monitoring device 3 and outputs a report of the monitoring results to the administrator terminal 4. The management server 2 also calculates the energy consumption of the facility and each piece of equipment, and outputs a report of the calculation results to the administrator terminal 4. The management server 2 also manages the setting values of each piece of equipment, estimates the optimum setting value of the equipment, and outputs a report of the estimation results to the administrator terminal 4.

In this embodiment, the management server 2 alone corresponds to the facility management system according to the present invention, but the facility management system according to the present invention includes one or more of the management server 2, the monitoring device 3, and the administrator terminal 4. It may also include components. For example, when the components of the management server 2, monitoring device 3, and administrator terminal 4 work together to share and execute facility management processing (see FIGS. 11 and 12), the processing is executed. A system including a plurality of components can be regarded as a facility management system according to the present invention. For example, the management server 2, the monitoring device 3, and the administrator terminal 4 may constitute a facility management system according to the present invention. Further, the management server 2 may also have the functions of the monitoring device 3. In this case, the management server 2 and the administrator terminal 4 may constitute the facility management system according to the present invention.

[Monitoring device 3]
As shown in FIG. 1, the monitoring device 3 is a server that includes a control section 31, a storage section 32, an operation display section 33, a communication I/F 34, and the like. Note that the monitoring device 3 is not limited to one computer, but may be a computer system in which a plurality of computers work together, or may be configured as a cloud server. Furthermore, various processes executed by the monitoring device 3 may be executed in a distributed manner by one or more processors. The monitoring device 3 uses BACnet to monitor equipment to be monitored installed in each of a plurality of facilities. The functions of the monitoring device 3 may be included in the management server 2.

The communication I/F 34 connects the monitoring device 3 to the communication network NW by wire or wirelessly, and executes data communication according to a predetermined communication protocol with external devices such as the management server 2 via the communication network NW. It is a communication interface for Further, the communication I/F 34 performs data communication according to BACnet with the equipment to be monitored.

The operation display unit 33 is a user interface that includes a display unit such as a liquid crystal display or an organic EL display that displays various information, and an operation unit such as a mouse, keyboard, or touch panel that receives operations.

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

FIG. 2 is a diagram showing an example of the monitoring equipment information DB 321 corresponding to the predetermined facility B1. The monitoring equipment information DB 321 includes information such as a name (monitoring equipment name), monitoring item, unit, classification, etc. for each equipment to be monitored (monitored equipment) among the equipment installed in the facility B1. The monitored equipment registered in the monitored equipment information DB 321 has a communication function that can use BACnet, and periodically transmits data corresponding to the monitoring items to the control unit 31. Each piece of information registered in the monitoring equipment information DB 321 is registered in advance by the administrator of the facility B1, the service provider of the equipment management service, and the like.

FIG. 3 is a diagram showing an example of the facility data information DB 322 corresponding to the predetermined facility B1. The facility data information DB 322 includes information such as acquisition date and time, data name, detected value, and unit for each facility data acquired from the monitored equipment. The acquisition date and time is the date and time when facility data was acquired from the monitoring target equipment. The data name is a name given to facility data. The data name includes symbols, numbers, text information, and the like. FIG. 4 shows an example of the data name. The data name has no naming rule and is set by, for example, the manufacturer of the facility or equipment. The detected value is a measured value, a set value, or the like. For example, if the equipment to be monitored is an air conditioner, the detected value is the set temperature, and if the equipment to be monitored is a ventilation fan, the detected value is the ON or OFF setting state, and if the equipment to be monitored is a water heater. In this case, the detected value is the amount of water stored in the hot water tank.

Further, when the equipment to be monitored is an environmental sensor, the detected value is a detected value of the sensor. For example, if the environmental sensor is a temperature sensor that measures air temperature, the detected value is temperature (outside air temperature). For example, if the environmental sensor is a humidity sensor that measures humidity, the detected value is humidity (outside humidity). For example, if the environmental sensor is a sensor that measures the flow of people, the detected value is the number of people (number of visitors, etc.). For example, if the environmental sensor is a sensor that measures sunlight time, the detected value is the sunlight time (sunshine time).

In this way, the facility data information DB 322 includes various facility data including measurement data of the equipment in the facility B1 and environmental data corresponding to the facility B1. Further, the environmental data includes data regarding the weather, the flow of people in the facility B1, and the hours of sunlight. Note that the storage unit 32 stores a monitoring equipment information DB 321 and a facility data information DB 322 for each facility. That is, the monitoring device 3 can monitor multiple facilities.

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

For example, if the equipment to be monitored is a ventilation fan, it is possible for the user to adjust the output value (power consumption, current, etc.) by turning the ventilation fan on or off. In this case, the ON/OFF setting state of the ventilation fan is facility data that can be adjusted.

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

On the other hand, if the equipment to be monitored is an environmental sensor, the measured temperature (outside temperature), humidity (outside humidity), human flow, sunlight hours, etc. are output values depending on the environment and are data that cannot be adjusted. It is. Therefore, temperature (outside temperature), humidity (outside humidity), flow of people, and hours of sunlight are facility data that cannot be adjusted.

The control unit 31 includes control devices such as a CPU, ROM, and RAM. The CPU is a processor that executes various types of arithmetic processing. The ROM is a non-volatile storage unit that stores in advance control programs such as a BIOS and an OS for causing the CPU to execute various arithmetic processes. The RAM is a volatile or nonvolatile storage unit that stores various information, and is used as a temporary storage memory (work area) for various processes executed by the CPU. The control unit 31 controls the monitoring device 3 by causing the CPU to execute various control programs stored in advance in the ROM or storage unit 32.

Specifically, the control unit 31 acquires facility data such as measurement data and environmental data from each monitored equipment in each facility and stores it in the storage unit 32 (see FIG. 3).

As the monitoring device 3, well-known technology such as a building automatic management control system using BACnet can be applied.

However, with conventional technology, it is difficult to configure settings for optimizing energy consumption of equipment within a facility using various data related to the facility (adjustable data, non-adjustable data, etc.). be. On the other hand, the facility management system 1 according to the present embodiment can optimize the energy consumption of the facility by using various data regarding the facility, as described below.

[Management server 2]
As shown in FIG. 1, the management server 2 is a server that includes a control section 21, a storage section 22, an operation display section 23, a communication I/F 24, and the like. Note that the management server 2 is not limited to one computer, but may be a computer system in which a plurality of computers work together, or may be configured as a cloud server. Furthermore, various processes executed by the management server 2 may be executed in a distributed manner by one or more processors.

The communication I/F 24 connects the management server 2 to the communication network NW by wire or wirelessly, and communicates with external devices such as the monitoring device 3 and the administrator terminal 4 via the communication network NW according to a predetermined communication protocol. It is a communication interface for executing data communication.

The operation display unit 23 is a user interface that includes a display unit such as a liquid crystal display or an organic EL display that displays various information, and an operation unit such as a mouse, keyboard, or touch panel that receives operations.

The storage unit 22 is a nonvolatile storage unit such as an HDD or an SSD that stores various information. Specifically, the storage unit 22 includes an adjustment availability information database (hereinafter referred to as adjustment availability information DB) 221.

FIG. 5 is a diagram showing an example of the adjustment availability information DB 221 corresponding to the facility B1. The adjustment possibility information DB 221 includes information such as acquisition date and time, data name, detected value, unit, adjustment possibility, etc. for each facility data (measurement data, environmental data, etc.) acquired from the monitored equipment. Each piece of information in the adjustment possibility information DB 221 may be obtained by adding adjustment possibility information to each piece of information stored in the facility data information DB 322 (see FIG. 3) of the monitoring device 3. The adjustment possibility is identification information (flag) that identifies whether the output value is adjustable or not. For example, if the facility data is the set temperature of an air conditioner, the set temperature can be adjusted by the user operating the air conditioner, so "1" indicating that it is adjustable is registered in the facility data. Ru. For example, if the facility data is the temperature measured by a temperature sensor (outside temperature), the temperature cannot be adjusted, so "0" indicating that it cannot be adjusted is registered in the facility data. .

Based on the facility data acquired from the monitoring device 3, the control unit 21 identifies whether the facility data is adjustable data or non-adjustable data, and registers the identification result in the adjustable availability information DB 221. do.

In addition, as another embodiment, part or all of the adjustment availability information DB 221 may be stored in another server accessible from the management server 2 via the communication network NW. In this case, the control unit 21 of the management server 2 may acquire the information from the other server and execute various processes such as a facility management process (see FIGS. 11 and 12) described later.

The storage unit 22 also stores data for generating various web pages such as the recommended setting page P1 (see FIGS. 9 and 10) displayed on the administrator terminal 4. In addition, in this embodiment, the control unit 21 of the management server 2 generates the various web pages and transmits the information of the web pages to the administrator terminal 4, thereby transmitting the various web pages to the administrator terminal 4. It is possible to display the page. Further, in another embodiment, the control unit 21 of the management server 2 transmits data necessary for displaying the various web pages to the administrator terminal 4. The various web pages may be displayed.

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

The control unit 21 includes control devices such as a CPU, ROM, and RAM. The CPU is a processor that executes various types of arithmetic processing. The ROM is a non-volatile storage unit that stores in advance control programs such as a BIOS and an OS for causing the CPU to execute various arithmetic processes. The RAM is a volatile or nonvolatile storage unit that stores various information, and is used as a temporary storage memory (work area) for various processes executed by the CPU. The control unit 21 controls the management server 2 by executing various control programs stored in advance in the ROM or storage unit 22 on the CPU.

Specifically, the control unit 21 includes various processing units such as an acquisition processing unit 211, an identification processing unit 212, an estimation processing unit 213, and an output processing unit 214, as shown in FIG. The control unit 21 functions as the various processing units by causing the CPU to execute various processes according to the facility management program. Further, a part or all of the processing section may be constituted by an electronic circuit. Note that the facility management program may be a program for causing a plurality of processors to function as the processing units.

The acquisition processing unit 211 acquires facility data including measurement data of equipment in the facility B1 and environmental data corresponding to the facility B1. For example, the acquisition processing unit 211 acquires facility data stored in the facility data information DB 322 (see FIG. 3) from the monitoring device 3. As another embodiment, the acquisition processing unit 211 may directly acquire the facility data from the equipment in the facility B1. Further, the acquisition processing unit 211 may acquire environmental data from an institution outside the facility B1. For example, the acquisition processing unit 211 may acquire meteorological data (temperature, humidity, sunlight hours, etc.) according to the region of the facility B1 from a public institution. The acquisition processing unit 211 registers information on the acquired facility data (date and time of acquisition, data name, detected value, unit) in the adjustment availability information DB (see FIG. 5). The adjustment availability information DB stores facility data (historical data) for a predetermined period of time in the past.

The identification processing unit 212 executes identification processing for identifying whether each of the facility data acquired by the acquisition processing unit 211 is adjustable data or non-adjustable data. Specifically, the identification processing unit 212 determines whether the facility data is adjusted based on at least one of the following information included in the facility data: acquisition date and time, data name, detected value (numeric value, ON/OFF), and unit. Identify whether the data is possible or non-adjustable.

For example, if the data name of the facility data (see FIG. 4) includes the term "temperature setting" and the facility data includes a unit of "degrees" or "℃", the identification processing unit 212 Identify the facility data as adjustable data. For example, if the data name of the facility data includes the term "ON" or "OFF," the identification processing unit 212 identifies the facility data as data that can be adjusted.

For example, if the data name of the facility data includes the term "outside temperature" or "outside humidity," the identification processing unit 212 identifies the facility data as data that cannot be adjusted. For example, if the data name of the facility data includes a unit of number of people (number of visitors, etc.), the identification processing unit 212 identifies the facility data as data that cannot be adjusted. For example, if the data name of the facility data includes the term "solar radiation time" and the facility data includes a unit of time, the identification processing unit 212 determines that the facility data is non-adjustable data. Identify that there is.

In another embodiment, the identification processing unit 212 identifies whether the facility data is adjustable data or non-adjustable data by performing machine learning using the past facility data. Good too. For example, as shown in FIG. 6, a plurality of past facility data are input to the learning section A of the identification processing section 212. The data input to learning section A includes data (teacher data) to which identification information (flag) identifying whether or not adjustment is possible is attached, and data to which the identification information is not attached. It's okay. The learning unit A performs machine learning on these input data to generate a learned model that estimates whether the facility data is adjustable or non-adjustable. The identification unit A of the identification processing unit 212 uses a learned model learned by machine learning to identify whether the acquired facility data is adjustable data or non-adjustable data. Note that, in each of the learning stage and the usage stage, the identification unit A uses the learned model to identify whether the facility data of the facility B1 is adjustable data or non-adjustable data. .

Note that a well-known method can be applied to the machine learning method. For example, machine learning includes algorithms such as supervised learning using supervised data, unsupervised learning using unsupervised data, and reinforcement learning. To achieve this, a method called ``deep learning'' is used that learns to extract the feature values themselves.

In another embodiment, the identification processing unit 212 performs machine learning using the facility data of a plurality of past facilities to determine whether the facility data of the specific facility B1 is adjustable or non-adjustable. It may also be possible to identify whether the data is For example, as shown in FIG. 7, the past facility data of each of the plurality of facilities B1, B2, . . . , Bn is input to the learning section A of the identification processing section 212. The data input to learning section A includes data (teacher data) to which identification information (flag) identifying whether or not adjustment is possible is attached, and data to which the identification information is not attached. It's okay. The learning unit A performs machine learning on these input data to generate a learned model that estimates whether the facility data is adjustable or non-adjustable. The identification unit A of the identification processing unit 212 uses a learned model learned by machine learning to identify whether the facility data of the facility B1 is adjustable data or non-adjustable data.

The identification processing unit 212 registers the identification result of the identification process in association with the facility data. For example, when the identification processing unit 212 identifies that the facility data is data that can be adjusted, the identification processing unit 212 adds "1" to the facility data, which indicates that it is adjustable, in the adjustment availability information DB 221 (see FIG. 5). Associate and register. For example, when the identification processing unit 212 identifies that the facility data is data that cannot be adjusted, the identification processing unit 212 associates "0" indicating that adjustment is not possible with the facility data in the adjustment availability information DB 221. and register.

The estimation processing unit 213 includes adjustable facility data (first facility data of the present invention) corresponding to a predetermined facility (first facility of the present invention) and non-adjustable facility data (first facility data of the present invention) related to the facility data. The second facility data of the invention) is used to estimate the optimal setting value of the facility data corresponding to the facility.

For example, the estimation processing unit 213 determines the optimum temperature of the air conditioner based on the past set temperature of the air conditioner in facility B1 and environmental data that influences the set temperature (outside temperature, outside humidity, human flow, sunlight hours, etc.). Estimate the set temperature. For example, the estimation processing unit 213 may also calculate the past setting state (ON/OFF) of the ventilation fan in facility B1 and the environmental data that influences the setting state (outside temperature, outside humidity, human flow, sunlight hours, etc.). Based on this, the optimal setting state (ON/OFF) of the ventilation fan is estimated. Further, for example, the estimation processing unit 213 may calculate the amount of water stored in the water heater of the facility B1 based on the past set water storage amount and environmental data that influences the set water storage amount (outside temperature, outside humidity, human flow, sunlight hours, etc.). , estimate the optimal water storage setting for the water heater.

Here, a specific method for estimating the optimum setting value will be explained using the setting temperature of an air conditioner as an example.

For example, as shown in FIG. 8, the learning unit B of the estimation processing unit 213 stores a plurality of past adjustable facility data and unadjustable facility data of the facility B1, and past energy consumption of the facility B1 (for example, an air conditioner). The target value of power consumption) is input. The learning unit B learns non-adjustable facility data related to adjustable facility data among the non-adjustable facility data. Specifically, the learning unit B identifies (learns) facility data having a change characteristic corresponding to a change characteristic of the adjustable facility data among the non-adjustable facility data. For example, in past facility data, if the outside temperature, which is facility data that cannot be adjusted, has increased from D1 degrees to D2 degrees, and the air conditioner setting temperature has been lowered from T1 to T2, the learning section B determines that the outside temperature is related to the set temperature of the air conditioner. For example, in past facility data, when the flow of people (number of visitors), which is facility data that cannot be adjusted, increases from M1 (people) to M2 (people), the set temperature of the air conditioner is T1 (degrees). to T2 (degrees), the learning unit B determines that the flow of people is related to the set temperature of the air conditioner.

In this way, the estimation processing unit 213 selects non-adjustable facility data that has change characteristics corresponding to change characteristics of adjustable facility data (measured data) out of non-adjustable facility data (for example, environmental data). Identify. In the above example, the estimation processing unit 213 corresponds to the change characteristics (rise and fall changes) of the set temperature that can be adjusted out of the environmental data that cannot be adjusted (outside temperature, outside humidity, human flow, sunlight hours, etc.). Identify outside temperature with changing characteristics. The estimation processing unit 213 may specify one piece of facility data (for example, outside temperature) that cannot be adjusted, or may specify a plurality of facility data (such as outside temperature, human flow, etc.). Furthermore, the estimation processing unit 213 may learn the correlation between adjustable facility data and non-adjustable facility data using a plurality of past facility data.

Furthermore, the learning unit B learns the set temperature at which the power consumption of the air conditioner satisfies the target value based on past facility data. For example, the learning section B determines whether the set temperature is the target value of power consumption based on the power consumption for each set temperature, such as power consumption when the set temperature of the air conditioner is T1, power consumption when the set temperature of the air conditioner is T2, etc. Learn whether it satisfies or not. The learning unit B performs machine learning on these input data to generate a learned model that estimates the optimal setting value (optimum temperature setting) of adjustable data (in this case, the temperature setting of the air conditioner).

The estimation unit B of the estimation processing unit 213 estimates the optimal setting value for the current setting value of the equipment using the learned model learned by machine learning. The estimation unit B receives the current adjustable facility data and non-adjustable facility data of the facility B1, and the current target value of energy consumption of the facility B1. For example, estimation part B contains the current set temperature of the air conditioner (adjustable facility data) and the current environmental data related to the set temperature (outside temperature, outside humidity, human flow, sunlight hours, etc.) (unadjustable facility data). Facility data) and the current target value of power consumption of the air conditioner are input. Estimating unit B uses a trained model learned by machine learning to estimate the current outside temperature based on, for example, the current set temperature of the air conditioner, the current outside temperature, and the current target value of the power consumption of the air conditioner. In this step, an optimal set temperature (optimum set value) that satisfies the target value is estimated.

In this way, the estimation processing unit 213 determines the optimal setting for the energy consumption of the equipment corresponding to the adjustable facility data to satisfy the target value, based on the correlation between the adjustable facility data and the non-adjustable facility data. Estimate the value. Furthermore, the estimation processing unit 213 estimates the optimum setting value corresponding to the current environmental data.

The output processing unit 214 outputs the estimation result of the estimation processing unit 213. Specifically, the output processing unit 214 presents the optimal setting value to the administrator terminal 4. For example, as shown in FIG. 9, the output processing unit 214 causes the administrator terminal 4 to display a recommended setting page P1. The recommended settings page P1 displays equipment information such as the name of the facility, installation location of the target equipment, display name, and equipment name, and setting information such as current settings, recommended settings, and power consumption reduction amount. For example, if the equipment is an air conditioner, the current set temperature ("25°C") is displayed in the current setting value, and the optimum set temperature ("21°C") estimated by the estimation processing unit 213 is displayed in the recommended setting value. ") is displayed, and the expected reduction amount ("10%") of power consumption that will be reduced if the power consumption reduction amount is changed to the recommended setting value is displayed.

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

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

FIG. 10 shows another example of the recommended setting page P1. The recommended setting page P1 shown in FIG. 10 includes information such as current setting values, recommended setting values, and power consumption reduction amounts corresponding to each of a plurality of target facilities. The control unit 21 controls each of the facilities in the facility B1 based on the target value of energy consumption (target power consumption) set for the facility B1 and the current adjustable facility data and non-adjustable facility data. Estimate the optimal settings for equipment. Furthermore, the control unit 21 calculates the amount of power consumption reduction for each piece of equipment. Then, the control unit 21 controls the target power consumption based on the current power consumption (“W1”) of the entire facility B1, the target power consumption (“W0”), and the amount of power consumption reduction of each equipment. Calculate the achievement rate. In this way, the control unit 21 may collectively estimate the recommended setting values of a plurality of pieces of equipment in the facility B1.

The control unit 21 may output an instruction to change the setting value to each target equipment when the administrator selects the "Batch setting change" button on the recommended setting page P1 shown in FIG. 10. Each piece of equipment may change the setting value in response to a setting change operation by the administrator, or may change the setting value in response to a change instruction obtained from the control unit 21.

[Administrator terminal 4]
As shown in FIG. 1, the administrator terminal 4 includes a control section 41, a storage section 42, an operation display section 43, a communication I/F 44, and the like. The administrator terminal 4 is, for example, an information processing device such as a smartphone, a tablet terminal, or a personal computer.

The communication I/F 44 connects the administrator terminal 4 to the communication network NW by wire or wirelessly, and executes data communication according to a predetermined communication protocol with external devices such as the management server 2 via the communication network NW. It is a communication interface for

The operation display unit 43 is a user interface that includes a display unit such as a liquid crystal display or an organic EL display that displays information such as various web pages, and an operation unit such as a mouse, keyboard, or touch panel that receives operations. .

The storage unit 42 is a nonvolatile storage unit such as an HDD, SSD, or flash memory that stores various information. For example, the storage unit 42 stores a control program such as a browser program. Specifically, the browser program is a control program for causing the control unit 41 to execute communication processing with an external device such as the management server 2 according to a communication protocol such as HTTP (Hypertext Transfer Protocol). Further, the browser program may be a dedicated application for executing communication processing with the management server 2 according to a predetermined communication protocol.

The control unit 41 includes control devices such as a CPU, ROM, and RAM. The CPU is a processor that executes various types of arithmetic processing. The ROM is a nonvolatile storage unit in which control programs such as a BIOS and an OS for causing the CPU to execute various processes are stored in advance. The RAM is a volatile or nonvolatile storage unit that stores various information, and is used as a temporary storage memory (work area) for various processes executed by the CPU. The control unit 41 controls the administrator terminal 4 by executing various control programs stored in advance in the ROM or storage unit 42 on the CPU.

Specifically, the control unit 41 functions as a browser processing unit 411 by executing various processes according to the browser program stored in the storage unit 42. The browser processing unit 411 can execute a browser process that causes the operation display unit 43 to display a web page provided from the management server 2 via the communication network NW, and inputs an operation on the operation display unit 43 to the management server 2. It is possible. That is, the administrator terminal 4 can function as an operating terminal for the management server 2 by executing the browser program by the control unit 41. Note that a part or all of the processing units included in the control unit 41 may be composed of electronic circuits.

For example, in the administrator terminal 4, when a user operation is performed to request access to a predetermined URL corresponding to the facility management service site of the facility management service provided by the facility management system 1, the control unit 41 acquires the data of the web page of the facility management service site from the management server 2 and causes the operation display section 43 to display the web page of the facility management service site. Note that, for example, the access request to the predetermined URL is performed by a selection operation from a list of pre-registered websites, a selection operation from search results on an information search site, a text input operation, or the like. In addition, if a dedicated application corresponding to the management server 2 is installed on the administrator terminal 4, the administrator of the administrator terminal 4 can display the equipment on the operation display section 43 by performing an operation to start the dedicated application. The web page of the management service site is displayed.

For example, when using the facility management service, the administrator of facility B1 enters login information (ID, password) into the login page (not shown) of the facility management service site displayed on the administrator terminal 4. . When the login information is authenticated, the control unit 41 causes the operation display unit 43 to display various web pages (for example, recommended setting page P1 (see FIGS. 9 and 10)).

[Facility management processing]
Hereinafter, facility management processing executed in the facility management system 1 will be described with reference to FIGS. 11 and 12. Specifically, in this embodiment, the facility management process is executed by the control unit 21 of the management server 2.

Note that the present invention can be regarded as an invention of a facility management method that executes one or more steps included in the facility management process. Furthermore, one or more steps included in the facility management process described here may be omitted as appropriate. Note that each step in the facility management process may be executed in a different order as long as similar effects are produced. Furthermore, although the case where the control unit 21 executes each step in the facility management process will be described as an example, there is a facility management method in which one or more processors execute each step in the facility management process in a distributed manner. Other embodiments are also possible.

FIG. 11 is a flowchart illustrating an example of the procedure of the learning stage of the estimation process for estimating the optimal setting value in the facility management process.

First, in step S11, the control unit 21 acquires past facility data corresponding to each piece of equipment in a plurality of facilities. For example, the control unit 21 acquires facility data (date and time of acquisition, data name, detected value, unit, etc.) from the facility data information DB 322 (see FIG. 3) for each facility (see FIG. 7).

Next, in step S12, the control unit 21 performs machine learning using past facility data corresponding to the equipment of each of the plurality of facilities to generate a learned model. For example, the control unit 21 performs machine learning on facility data (teacher data) to which identification information (flag) for identifying whether adjustment is possible is attached and facility data to which the identification information is not attached. , a trained model is generated that estimates whether the target facility data is adjustable data or non-adjustable data (see FIG. 7).

Next, in step S13, the control unit 21 acquires past facility data corresponding to the equipment of the target facility B1. For example, the control unit 21 acquires facility data (date and time of acquisition, data name, detected value, unit, etc.) from the facility data information DB 322 (see FIG. 3) of the facility B1 (see FIG. 7).

Next, in step S14, the control unit 21 determines whether the facility data corresponding to facility B1 is adjustable data or non-adjustable data, using the learned model learned by machine learning. (See Figure 7).

Next, in step S15, the control unit 21 acquires a target value of past energy consumption of the facility B1. For example, when the target equipment is an air conditioner, the control unit 21 acquires a target value of energy consumption (power consumption) of the air conditioner (see FIG. 8). The control unit 21 acquires target values set in the past by the administrator.

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

Next, in step S17, the control unit 21 performs machine learning using the target value of energy consumption, the adjustable facility data, and the non-adjustable facility data to generate a learned model. For example, the control unit 21 performs machine learning using the target value of energy consumption corresponding to the facility B1, the adjustable facility data and the non-adjustable facility data corresponding to the facility B1, and A trained model is generated that estimates the optimal settings for the equipment (see Figure 8).

Specifically, the control unit 21 learns non-adjustable facility data related to adjustable facility data (measured data) among non-adjustable facility data (for example, environmental data) in the facility B1. For example, the control unit 21 responds to the change characteristics (increase and decrease changes) of the set temperature of the adjustable air conditioner in the past out of non-adjustable environmental data (outside temperature, outside humidity, human flow, sunlight hours, etc.). Identify outside temperature with changing characteristics. That is, the control unit 21 uses a plurality of past facility data to learn the correlation between adjustable facility data and non-adjustable facility data.

Furthermore, the control unit 21 learns an optimal setting value that allows the energy consumption of the equipment to satisfy the target value, based on past facility data in the facility B1. For example, the control unit 21 learns whether the set temperature satisfies the target value of power consumption based on the power consumption for each set temperature of the air conditioner. The control unit 21 uses machine learning to generate a learned model that estimates the optimal setting value (optimum temperature setting) of adjustable data (for example, the temperature setting of an air conditioner) (see FIG. 8).

The learned model (optimum setting value estimation model) generated in the above learning stage is stored in the storage unit 22.

FIG. 12 is a flowchart illustrating an example of a process procedure in the usage stage of the estimation process for estimating the optimal setting value in the facility management process.

First, in step S21, the control unit 21 acquires current facility data corresponding to the target facility B1. For example, the control unit 21 acquires current facility data (date and time of acquisition, data name, detected value, unit, etc.) from the facility data information DB 322 (see FIG. 3) corresponding to the facility B1.

Next, in step S22, the control unit 21 uses the learned model generated in step S12 to determine whether the acquired current facility data is adjustable facility data or non-adjustable facility data. identify.

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

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

Next, in step S25, the control unit 21 uses the learned model (optimal setting value estimation model) generated in step S17 to determine the current target value of energy consumption and the current adjustable facility data. and the current non-adjustable facility data, the optimal setting value of the target equipment in facility B1 is estimated (see FIG. 8). For example, the control unit 21 uses the learned model to estimate the optimal set temperature based on the current set temperature of the air conditioner, the current outside temperature, and the current target value of the power consumption of the air conditioner.

Finally, in step S26, the control unit 21 outputs the estimation result. For example, as shown in FIGS. 9 and 10, the control unit 21 causes the administrator terminal 4 to display a recommended setting page P1, and causes the estimated optimal setting temperature to be displayed on the recommended setting page P1. As described above, the control unit 21 executes the facility management process.

As described above, the facility management system 1 according to the present embodiment includes an acquisition processing unit 211 that acquires facility data including measurement data of equipment in the facility and environmental data corresponding to the facility; an identification processing unit 212 that identifies, for each of the acquired facility data, whether the data is data whose output value can be adjusted by a setting operation of the equipment or data whose output value cannot be adjusted by a setting operation of the equipment; , estimating an optimal setting value of the first facility data based on adjustable first facility data corresponding to the first facility and non-adjustable second facility data related to the first facility data. A processing unit 213 is provided.

According to the above configuration, not only measurement data of the equipment but also detection data of various sensors installed in the facility (environmental data, etc.) is obtained from outside the facility (sensors installed outside the facility, external organizations, the Internet, etc.) Environmental data (such as weather data) can also be used to estimate the optimal settings for equipment. Therefore, it becomes possible to optimize the energy consumption of the facility using various data regarding the facility.

Note that the environmental data may include data regarding weather, the flow of people in the facility, and sunlight hours.

In addition, in the facility management system 1, the identification processing unit 212 determines whether the facility data can be adjusted based on at least one of the following information: date and time, name, numerical value, ON/OFF, and unit included in the facility data. or non-adjustable data may be identified. Thereby, it is possible to identify whether the facility data is data that can be easily adjusted or data that cannot be adjusted.

In the facility management system 1, the identification processing unit 212 performs machine learning using the past facility data corresponding to each of the plurality of facilities to determine whether the facility data is adjustable or adjustable. It may also be possible to identify whether the data is impossible. Thereby, it is possible to identify whether the facility data is data that can be reliably adjusted or data that cannot be adjusted.

In addition, in the facility management system 1, the estimation processing unit 213 selects the facility data having change characteristics corresponding to the change characteristics of the past first facility data among the facility data that cannot be adjusted to the second facility. It may be specified as data. Further, the estimation processing unit 213 may use the past facility data acquired by the acquisition processing unit 211 to learn the correlation between the first facility data and the second facility data.

Further, in the facility management system 1, the estimation processing unit 213 determines that the energy consumption of the equipment corresponding to the first facility data is a target value based on the correlation between the first facility data and the second facility data. The optimal setting value satisfying the following may be estimated. Furthermore, the estimation processing unit 213 may estimate the optimal setting value corresponding to the current environmental data acquired by the acquisition processing unit 211. Thereby, it is possible to estimate the optimal setting value according to the current environment.

In addition, the facility management system 1 automatically determines which points are controllable or uncontrollable from past facility data and current facility data, and compares them with the secular data of energy consumption to determine which points are controllable. This system proposes settings that will minimize energy consumption. The facility management system 1 also includes an identification unit that identifies controllable and uncontrollable points, and learns how to set controllable points using past energy consumption data. The proposed estimation unit is also provided. In the estimation section, settings may be made to not only reduce energy consumption but also to maintain a constant level of comfort (humidity, room temperature, etc.), carbon dioxide concentration, etc.

1: Facility management system 2: Management server 3: Monitoring device 4: Administrator terminal 21: Control unit 211: Acquisition processing unit 212: Identification processing unit 213: Estimation processing unit 214: Output processing unit 411: Browser processing unit DB 221: Adjustment Availability information DB321: Monitoring equipment information DB322: Facility data information

Claims (10)

an acquisition processing unit that acquires facility data including measurement data of equipment in the facility and environmental data corresponding to the facility;
an identification processing unit that identifies whether each of the facility data acquired by the acquisition processing unit is data whose output value can be adjusted or data whose output value cannot be adjusted;
Estimation processing that estimates the optimal setting value of the first facility data based on adjustable first facility data corresponding to the first facility and non-adjustable second facility data related to the first facility data. Department and
A facility management system equipped with The environmental data includes data regarding the weather, the flow of people in the facility, and the hours of sunlight.
The facility management system according to claim 1. The identification processing unit determines whether the facility data is adjustable or non-adjustable based on at least one of date and time, name, numerical value, ON/OFF, and unit included in the facility data. identify whether the data is
The facility management system according to claim 1 or 2. The identification processing unit determines whether the facility data is adjustable or non-adjustable data by performing machine learning using the past facility data corresponding to each of the plurality of facilities. identify,
The facility management system according to any one of claims 1 to 3. The estimation processing unit specifies, as the second facility data, the facility data having a change characteristic corresponding to the change characteristic of the first facility data in the past, among the facility data that cannot be adjusted.
The facility management system according to any one of claims 1 to 4. The estimation processing unit learns a correlation between the first facility data and the second facility data using the past facility data acquired by the acquisition processing unit.
The facility management system according to any one of claims 1 to 5. The estimation processing unit estimates the optimal setting value, based on the correlation between the first facility data and the second facility data, so that the energy consumption of the equipment corresponding to the first facility data satisfies a target value. do,
The facility management system according to claim 6. The estimation processing unit estimates the optimal setting value corresponding to the current environmental data acquired by the acquisition processing unit.
The facility management system according to any one of claims 1 to 7. one or more processors,
an acquisition step of acquiring facility data including measurement data of equipment in the facility and environmental data corresponding to the facility;
an identification step of identifying whether each of the facility data acquired in the acquisition step is data whose output value can be adjusted or data whose output value cannot be adjusted;
Estimating an optimal setting value of the first facility data based on adjustable first facility data corresponding to the first facility and non-adjustable second facility data related to the first facility data. and,
Facility management method to carry out. an acquisition step of acquiring facility data including measurement data of equipment in the facility and environmental data corresponding to the facility;
an identification step of identifying whether each of the facility data acquired in the acquisition step is data whose output value can be adjusted or data whose output value cannot be adjusted;
Estimating an optimal setting value of the first facility data based on adjustable first facility data corresponding to the first facility and non-adjustable second facility data related to the first facility data. and,
A facility management program that causes one or more processors to execute