WO2016051477A1

WO2016051477A1 - Service system and method for assisting improvement of air-conditioning of building

Info

Publication number: WO2016051477A1
Application number: PCT/JP2014/075947
Authority: WO
Inventors: 鈴木　勝幸
Original assignee: 株式会社日立製作所
Priority date: 2014-09-29
Filing date: 2014-09-29
Publication date: 2016-04-07

Abstract

Proposed is a service system and method for assisting improvement of the space within a building, said system and method being capable of offering an optimum improvement method for enhancing the comfort of the space within a building, taking into account the behavior of the residents. A renovation simulation according to the present invention is performed for each of a plurality of predetermined specifications for each of a plurality of given renovation items of a building, wherein the renovation simulation receives at least one process signal representing environmental data that affects the comfort of the space within the building, and at least one event signal representing information relating to the behavior of the residents, and determines, on the basis of these signals, components of the process signal that correspond to variation factors and that occur when each renovation item of the building is renovated to each predetermined specification for the renovation item. Based on these results, an assessment value is calculated for each predetermined specification for each renovation item, and a renovation plan for the building is created on the basis of the calculated assessment value for each specification for each renovation item. In this renovation simulation, the variation components of the process signal that arise due to the behavior of the residents are excluded when determining the components of the process signal that correspond to the variation factors.

Description

Building air conditioning improvement support service system and method

The present invention relates to a building space improvement support service system and method, and is particularly suitable for application to a building air conditioning improvement support service system that supports building improvement.

Buildings and homes require air conditioning control that takes comfort into consideration in addition to cooling and heating efficiency and energy-saving characteristics. In the following, an energy management system for buildings is called BEMS (Building Energy Management System), and an energy management system for houses is called HEMS (Home Energy Management System).

In recent years, with regard to air conditioning control, the realization of advanced information processing functions by improving computer processing capacity has expanded the scope of automatic control such as whole building heating and remote operation. In areas where central heating is the main air conditioning means, in addition to heat source control, individual control, that is, local control for each room of the radiator and air conditioner is common.

In recent years, technology for optimizing the schedule operation of heat sources such as boilers and heat pumps has been realized by increasing the functionality of thermostats. In addition, a technology has been realized that measures resident behavior and stops air conditioning when the resident is absent. For example, Patent Document 1 discloses a system that predicts a change pattern of the outside air temperature based on the next day's weather information acquired from an external weather information site or the like, and controls two types of heating devices based on the change pattern. It is disclosed. Patent Document 2 discloses a system that performs air conditioning control by determining the comfort / discomfort of each room based on the temperature and humidity inside the house and also provides power-saving advice to residents. Further, Patent Document 3 discloses a system that measures the temperature inside and outside the house and the electricity consumption of the air conditioning equipment and analyzes the degree of deterioration of the heat insulation performance of the house and the performance of the air conditioning equipment.

In recent years, building models have been developed to evaluate the appropriateness of heat insulation characteristics and heat source capacity that influence the characteristics of air conditioning control, and the standardization process is also progressing. As such a building model, for example, building thermal characteristic models as shown in Non-Patent Document 1 and Non-Patent Document 2 are known. Predictive control using these building thermal characteristic models is also being performed, and in air conditioning control of buildings, air conditioning control considering comfort in addition to cooling / heating efficiency and energy saving characteristics is required. For example, Patent Document 4 discloses a technology for optimizing on / off control of a heat source boiler as control in consideration of such comfort. Further, Non-Patent Document 3 discloses that a power energy consumption tendency of home appliances and the like is grasped by analyzing power consumption characteristics in a building.

JP 2013-204834 A JP 2013-124794 A JP 2010-108108 A WO2013 / 171448 PREDICTIVE TEMPERATURE MANAGEMENT CONTROLLER

However, by introducing the above-described BEMS and HEMS, some ingenuity is required to improve the energy efficiency and comfort of the building. For example, in the invention disclosed in Patent Document 1, only an air conditioner and a regenerative heater are controlled based on temperature prediction, and temperature changes due to resident behavior are not considered. In addition, the air conditioning performance, that is, the thermal efficiency, is also affected by the heat insulation characteristics of the building. However, in Patent Document 1, only the relationship between the outside air temperature and the amount of heat supplied is used in predicting the change in room temperature, and it cannot be said that the influence of the building heat insulation characteristics is explicitly taken into consideration. Furthermore, the invention disclosed in Patent Document 1 does not cover buildings that are not equipped with two types of heating equipment.

Patent Document 2 discloses a system that performs air conditioning control by determining whether each room is pleasant or uncomfortable based on the temperature and humidity inside the house, and also provides power saving advice to residents. It has only been encouraged to improve comfort and has not yet shown its impact on thermal efficiency.

Furthermore, in Patent Document 3, the temperature inside and outside the house and the electricity consumption of the air conditioning equipment are measured and accumulated to analyze the heat insulation performance of the house and the deterioration degree of the performance of the air conditioning equipment. Not reached. In addition, Non-Patent Document 3 shows power energy consumption trends of household appliances and the like by analysis of power consumption characteristics in buildings, but analysis of temperature and humidity necessary for building air conditioning control is excluded. Yes.

As for the building model for evaluating the validity of the heat insulation capacity and the heat source capacity that influence the characteristics of the air conditioning control, the building heat characteristic model as shown in Non-Patent Document 1 and Non-Patent Document 2 is known. The average fuel consumption such as average or daily average is handled, and thermal efficiency evaluation considering the daily change in air conditioning demand has not been achieved. Furthermore, predictive control using such a building model has been developed, but this is limited to optimization of on / off control of the heat source boiler as shown in Patent Document 4.

As described above, in the conventional technology, the air conditioning control is optimization for each room, and it cannot be said that the energy consumption of the entire building is optimized. In addition, the measurement of the resident behavior is limited to the presence / absence determination, and it cannot be said that the air conditioning control considering the influence on room temperature and humidity is performed. Furthermore, it is difficult to determine whether building insulation renewal or boiler capacity renewal is more effective than air conditioning control optimization. As described above, the conventional technology alone has a problem that it is difficult to determine an optimal improvement method for improving the comfort of a building space in consideration of resident behavior.

The present invention has been made in consideration of the above points, and intends to propose a building space improvement support service system and method capable of presenting an optimal improvement method for improving the comfort of a building space in consideration of resident behavior. To do.

In order to solve this problem, in the present invention, in a building air-conditioning improvement support service system that provides a building air-conditioning improvement support service, a process signal including environmental data that affects the comfort of the building space of the building, and resident behavior And a component for each factor that causes variation in the process signal when the predetermined repair item of the building is repaired to a predetermined specification based on the input process signal and the event signal. And a renovation simulation execution unit for executing a renovation simulation for each of the specifications of a plurality of predetermined renovation items, and a predetermined renovation item of the building based on a simulation result of each renovation simulation Of the building when changed to the above specifications The change of the environmental data is determined for each of the specifications of the respective repair items, the evaluation value for each of the specifications of the respective repair items is calculated based on the obtained change of the environmental data, and each of the calculated repair items A renovation plan creation unit that creates a renovation plan for the building based on an evaluation value for each of the specifications, and the refurbishment simulation execution unit calculates a fluctuation component of the process signal due to resident behavior in the renovation simulation. A component for each variation occurrence factor of the excluded process signal is obtained.

According to the present invention, in the building air-conditioning improvement support service method executed by the building air-conditioning improvement support service system that provides the building air-conditioning improvement support service, the process includes environmental data that affects the comfort of the building space of the building. The signal and an event signal composed of information related to resident behavior are input, and the process signal changes when the predetermined repair item of the building is repaired to a predetermined specification based on the input process signal and the event signal. A first step of executing a renovation simulation for obtaining a component for each occurrence factor for each of the specifications of a plurality of predetermined renovation items, and a predetermined result of the building based on a simulation result of each renovation simulation When the repair items are changed to the specified specifications, respectively. Change of the environmental data of the building is determined for each of the specifications of each of the renovation items, and an evaluation value for each of the specifications of each of the renovation items is calculated based on the obtained change of the environmental data. And a second step of creating a renovation plan for the building based on an evaluation value for each specification of the refurbishment item. In the first step, the process signal of the process signal caused by resident behavior in the renovation simulation is provided. A component for each variation occurrence factor of the process signal excluding the variation component is obtained.

According to the present invention, it is possible to present an optimal renovation method that improves the comfort of a building in consideration of resident behavior.

It is a block diagram which shows the logic structure of the building air-conditioning improvement assistance service system by 1st Embodiment. It is a block diagram with which it uses for description of the specific processing content of a scenario setting process part. It is a block diagram with which it uses for description of the specific processing content of a repair simulation execution part. It is a block diagram with which it uses for description of the specific processing content of the repair plan preparation process part of the building air-conditioning improvement assistance service system by 1st Embodiment. It is a block diagram with which it uses for description of the specific processing content of the repair plan preparation part. It is a block diagram with which it uses for description of the specific processing content of the repair plan preparation part. It is a conceptual diagram which shows the structural example of the various data and signal in the building air-conditioning improvement assistance service system by 1st Embodiment. It is a flowchart which shows the process sequence of a series of processes performed in the building air-conditioning improvement assistance service system by 1st Embodiment regarding a building air-conditioning improvement assistance function. It is a flowchart which shows the specific process sequence of the decomposition process performed by the decomposition | disassembly part. It is a block diagram which shows the specific schematic structure of the building air-conditioning improvement assistance service system by 1st Embodiment. It is a block diagram which shows schematic structure at the time of applying the building air-conditioning improvement assistance service system by 1st Embodiment to central heating. It is a block diagram which shows the logic structure of the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a block diagram with which it uses for description of the specific processing content of the repair plan preparation process part by 2nd Embodiment. It is a block diagram with which it uses for description of the specific processing content of the repair plan preparation process part by 2nd Embodiment. It is a flowchart which shows the process sequence of a series of processes performed in the building air-conditioning improvement assistance service system by 2nd Embodiment regarding a building air-conditioning improvement assistance function. It is a block diagram with which it uses for description of the control target value production | generation method in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a block diagram with which it uses for description of the other control target value production | generation method in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a flowchart which shows the process sequence of the control target value production | generation process in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a block diagram with which it uses for description of the model parameter update method of the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a conceptual diagram which shows the data structure of the control parameter adjustment in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a conceptual diagram with which it uses for description of the signal decomposition | disassembly process in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a conceptual diagram with which it uses for description of the effect of the control target value production | generation method in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a conceptual diagram with which it uses for description of the effect of the repair plan assistance in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a conceptual diagram with which it uses for description of another effect of the repair plan assistance in the building air-conditioning improvement assistance service system by 2nd Embodiment. It is a block diagram with which it uses for description of the signal decomposition | disassembly process at the time of applying the building air-conditioning improvement assistance service system by 2nd Embodiment to central heating.

Hereinafter, an embodiment of the present invention will be described in detail with reference to the drawings.

(1) First Embodiment (1-1) Logical Configuration of Building Air Conditioning Improvement Support Service System According to this Embodiment In FIG. 1, 1 indicates a building air conditioning improvement support service system according to this embodiment as a whole. This building air-conditioning improvement support service system 1 includes changes in environmental data such as room temperature and humidity in the building that affect the comfort of the building space, and causes the fluctuations (building insulation characteristics, resident behavior, and air-conditioning characteristics). This is referred to below as the cause of fluctuation), and the information obtained from the analysis is used to improve the comfort of the building space while improving the air conditioning fuel costs (hereinafter referred to as the air conditioning fuel costs). It is equipped with a building air-conditioning improvement support function that presents to the user a renovation plan that can be reduced.

In practice, in the building air conditioning improvement support service system 1, the measured values such as the room temperature and humidity in the building and the measured values of the external temperature and humidity are given as process signals to the scenario setting unit 20 of the scenario setting processing unit 2. It is done. In the building air-conditioning improvement support service system 1, information related to the behavior of the resident such as the number of times of opening and closing the windows and doors, the opening / closing time, and on / off of the air conditioning is given to the scenario setting unit 20 as an event signal.

At this time, the scenario setting unit 20 is also given scenario information indicating the contents of the scenario 25 selected at that time. Here, the scenario 25 in the present specification defines conditions for executing a renovation simulation described later. For example, a scenario in which the external temperature is raised by 5 degrees from the current external temperature, A scenario for reducing the current external temperature by 3 degrees and a scenario for changing the number of times of opening and closing the window and the opening and closing time are prepared. Each scenario 25 includes scenario data that defines how much the value of which process signal or event signal is to be changed. For example, the scenario in which the external temperature is increased by 5 degrees from the current external temperature includes scenario data for increasing the value of the process signal corresponding to the external temperature by 5 degrees.

Thus, the scenario setting unit 20 adds the scenario data included in the scenario 25 to the process signal or event signal corresponding to the selected scenario 25 among the given process signals and event signals. Apply. In this manner, by adding the scenario data to the corresponding process signal or event signal, a repair simulation can be performed under conditions according to the scenario 25.

Then, the scenario setting unit 20 adds the scenario data to the corresponding process signal or event signal, and then processes the process signals such as room temperature and humidity that affect the comfort of the building space (hereinafter referred to as specific process signals as appropriate). ) Are output to the disassembly unit 10 of the repair simulation execution unit 3. Further, the scenario setting unit 20 outputs the event signal and a part of the process signal to the conversion unit 30 of the repair simulation execution unit 3.

The conversion unit 30 converts the event signal and a part of the process signal given from the scenario setting unit 20 into a signal of the same physical unit system as the specific process signal by using the building model set by the model setting unit 40. . Specifically, the conversion unit 30 converts, for example, a scenario signal indicating the number of times that a window or door has been opened and closed and an opening and closing time into a signal that indicates a change in room temperature due to the opening and closing of the window or door in time series. In addition, the scenario signal indicating the on / off of the air conditioning is converted into a signal indicating a change in room temperature due to the on / off of the air conditioning in time series. Then, the conversion unit 30 outputs the signal obtained by such conversion processing to the decomposition unit 10 as a conversion event signal and a conversion process signal.

The decomposition unit 10 eliminates the fluctuation component of the specific process signal caused by the resident behavior from the specific process signal given from the scenario setting unit 20 based on the conversion event signal and the conversion process signal given from the conversion unit 30. Are decomposed into components for each variation occurrence factor, and the obtained components for each variation occurrence factor are stored in the decomposition signal database 15 of the modification plan creation processing unit 4.

The above processing is the renovation simulation. In the building air-conditioning improvement support service system 1, the remodeling simulation is performed for each scenario, and each of the items that can be remodeled in advance for the building (insulation material, air-conditioning equipment, etc., hereinafter referred to as a renovation item). ) Repeatedly for each specification (material for thermal insulation, capacity for air conditioning equipment, etc.). The remodeling simulation for each remodeling item specification is performed by the model setting unit 40 setting the building model in the conversion unit 30 when the remodeling item of the target building is remodeled to the specification.

By the above processing, for example, when the renovation item is “insulation material”, the fluctuation of the specific process signal due to the resident behavior when the specification (material) is “material A”, “material B”,. A component for each factor of occurrence of fluctuations in the specific process signal after the components are excluded is obtained and stored in the decomposed signal database 15. It is obtained and stored in the decomposed signal database 15. Such a repair simulation process is executed in the same manner for all scenarios.

The decomposition signal database 15 also stores some process signals such as the external temperature. A method of using this process signal will be described later.

On the other hand, this building air-conditioning improvement support service system 1 has a cost (hereinafter referred to as a refurbishment cost) required for refurbishing the relevant part of the target building with the refurbishment item for each refurbishment item specification. A database (hereinafter referred to as a repair cost database) 65 in which information of the information is stored is held in advance. For example, if the renovation item is “insulation” or “air conditioning equipment”, the cost of this renovation is not limited to the unit price for each specification of the insulation or air conditioning equipment, but also the insulation and air conditioning equipment in the building. It also includes the cost required for renovation and construction to change to the material and air conditioning equipment.

Then, when all the above-described repair simulations by the repair simulation execution unit 3 are completed, the target selection unit 60 of the repair plan creation processing unit 4 refers to the repair cost database 65 and performs the repair specifying one specification of one repair item. A plan creation instruction is given to the repair plan creation unit 50. Thus, in accordance with the repair plan creation instruction, the repair plan creation unit 50 executes the repair plan for repairing the relevant part of the target building at that time to the specification of the repair item specified in the repair plan creation instruction. And a total cost and an evaluation value of a predetermined evaluation item in that case (in the following, it is assumed that it is the comfort of the building and the subsequent air-conditioning fuel cost when the renovation plan is executed).

Similarly, the target selection unit 60 also performs the process and the total cost when executing the renovation plan for refurbishing the renovation item of the building to the specification for each of the remaining refurbishment item specifications. When the refurbishment plan is executed, the renovation plan creation unit 50 calculates the comfort of the building and the subsequent air-conditioning fuel cost. Then, when the above calculation is completed for all specifications of all the repair items, the target selection unit 60 gives a repair plan creation instruction to the repair plan creation unit 50.

When such a renovation plan creation instruction is given, the refurbishment plan creation unit 50 has a high level of comfort when the renovation plan is executed for each refurbishment plan in which the man-hours and total costs are calculated as described above. The improvement plan 200 arranged in order from the lowest or the lowest air-conditioning fuel cost is created. Then, the modification plan creation unit 50 presents the modification plan 200 created in this way to the user by printout or screen display.

(1-2) Specific Processing Contents of Building Air Conditioning Improvement Support Service System (1-2-1) Specific Processing Contents of Scenario Setting Processing Unit FIG. 2 shows the configuration of the scenario setting processing unit 2. The scenario setting processing unit 2 includes at least a scenario setting unit 20. The scenario setting unit 20 includes a signal editing unit 21 corresponding to each of the process signal and the event signal. In the signal editing unit 21, scenario data included in the scenario at that time is added to the corresponding process signal or event signal. By adding, the process signal or event signal after scenario setting is calculated.

Specifically, the signal editing unit 21 sets S (t) as the value of the target process signal or event signal at time t, and sets the value of scenario data at time t included in the scenario as bias (t).

To calculate the process signal SS (t) or the event signal SS (t) after the scenario is set, and convert the calculated process signal SS (t) or the event signal SS (t) to the conversion unit 30 or the disassembly of the repair simulation execution unit 3 To the unit 10.

Note that there are process signals and event signals that do not require scenario data to be added depending on the contents of the scenario. However, the signal editing unit 21 directly converts the corresponding process unit and event signal into the corresponding conversion unit 30 or decomposition. To the unit 10.

For example, in the scenario of “increasing the external temperature by 5 degrees from the current external temperature”, the scenario data for increasing the external signal by 5 degrees is added only to the process signal of the measured value of the external temperature. These process signals and event signals are output to the corresponding conversion unit 30 or decomposition unit 10 as they are. In addition, in the case of a scenario that “changes the number of windows open / closed”, the scenario data is added only to the event signal indicating the number of windows open / closed, and other process signals and event signals are supported as they are. To the conversion unit 30 or the decomposition unit 10.

(1-2-2) Specific Processing Contents of the Modification Simulation Execution Unit FIG. 3 shows the configuration of the modification simulation execution unit 3. The modification simulation execution unit 3 includes a model parameter calculation unit 44 and a model parameter database 45 in addition to the model setting unit 40, the conversion unit 30, and the decomposition unit 10 described above.

The model parameter calculation unit 44 is based on data (hereinafter referred to as building data) 100 relating to the building, such as the building style, the total floor area, the floor plan, and the resident population of the target building at that time, given in advance. For each scenario 25, under the scenario 25 (under the condition of the renovation simulation), the above-described case where the relevant part of the building is renovated to each specification of each refurbishment item defined in the refurbishment cost database 65 is described above. Each parameter of the building model (building model set in the conversion unit) is calculated. In practice, this parameter can be calculated using the least square method or the method disclosed in the above-mentioned Patent Document 4 or the above-mentioned Non-Patent Document 1 or Non-Patent Document 2. Then, the model parameter calculation unit 44 stores the parameters calculated in this way in the model parameter database 45 as model parameters 45D.

The model setting unit 40 is notified from the scenario information indicating the contents of the current scenario 25 notified from the scenario setting unit 20 of the scenario setting processing unit 2 and the target selection unit 60 of the modification plan creation processing unit 4 as described later. The corresponding model parameter 45D is acquired from the model parameter database 45 based on the renovation item and its specification. Then, the model setting unit 40 generates a building model for converting the event signal and some process signals into the same physical unit as the specific process signal based on the acquired model parameter 45D, and converts the generated building model into the conversion unit Set to 30. The actual state of the building model is a transfer function, and in this embodiment, a Laplace transform function is applied as the transfer function. Therefore, in the case of this embodiment, the above-described model parameter calculation unit 44 calculates the gain and time constant of the Laplace transform function as the model parameter 45D.

The conversion unit 30 uses the building model set by the model setting unit 40 to convert an event signal having a physical unit different from the specific process signal and a part of the process signal into a signal having the same physical unit as the specific process signal. Perform the conversion process. Specifically, the conversion unit 30 uses the event signal and the process signal to be converted as the signal S160, and the building model (Laplace conversion function) set by the model setting unit 40 as M (s).

Thus, the signal S160 is converted into a signal S170 having the same physical unit as that of the specific process signal. By this signal conversion processing, for example, the event signal S160 indicating the number of opening and closing times and the opening and closing time of the window shown in FIG. 3 is converted into the conversion event signal S170 of FIG. become. However, the conversion event signal S170 is obtained from the target selection unit 60 of the renovation plan creation processing unit 4 under the conditions specified in the scenario 25 selected at that time, and the corresponding part of the target building is then modeled. It represents a change in room temperature due to opening / closing of the window when the modification item notified to the setting unit 40 and the specification are modified.

Based on the specific process signal S10 provided from the scenario setting unit 20 of the scenario setting processing unit 2 and the above-described conversion scenario signal and conversion process signal S170 provided from the conversion unit 30, the disassembling unit 10 In the case where the relevant part is modified to the modification item notified to the model setting unit 40 from the target selection unit 60 of the modification plan creation processing unit 4 and its specification, the fluctuation component due to the resident behavior is excluded from the specific process signal S10. Then, a decomposition process for decomposing the specific process signal S10 into components for each variation occurrence factor is executed.

A general signal decomposition technique such as Fourier transform can be applied to the decomposition process. In this embodiment, the specific process signal S10 is converted into a component for each factor of fluctuation using an independent component analysis method. Decompose. For example, when the specific process signal S10 is a measured value of the room temperature in the building, the decomposition unit 10 depends on the temperature change component S10A that depends on the thermal insulation characteristics of the building and an event such as opening / closing of a window. It decomposes into the temperature change component S10B. Then, the decomposition unit 10 stores the components for each variation occurrence factor of the specific process signal S10 obtained in this way in the decomposition signal database 15.

(1-2-3) Specific Processing Contents of the Modification Plan Creation Processing Unit FIG. 4 shows a specific configuration example of the modification plan creation processing unit 4. The repair plan creation processing unit is configured to include the target selection unit 60, the repair plan creation unit 50, the decomposition signal database 15, and the repair cost database 65 as described above. In FIG. 4, “case 1”, “case 2”, “case 3”,... Indicate components for each cause of fluctuation of the specific process signal obtained by the above-described renovation simulation.

The target selection unit 60 refers to the repair cost database 65 when the repair simulation is executed by the repair simulation execution unit 3, and selects one repair item from the specifications of each repair item registered in the repair cost database 65. And the specification is selected, and this is notified to the model setting unit 40 of the repair simulation execution unit 3 together with the repair simulation execution instruction. Thus, the model setting unit 40 acquires the model parameter 45D corresponding to the specification of the repair item notified at this time from the model parameter database 45 in accordance with the repair simulation execution instruction, and at that time, based on the acquired model parameter 45D as a target. A building model of the existing building is generated, and the generated building model is set in the conversion unit 30.

Further, the target selecting unit 60 thereafter gives the model setting unit 40 an instruction to execute the repair simulation while sequentially switching the specification of the repair item notified to the model setting unit 40 to the specification of the other repair item to be notified. In this way, under the control of the object selecting unit 60, the remodeling simulation execution unit 3 performs a remodeling simulation for each specification of each refurbishment item.

On the other hand, when all of the above-described repair simulations by the repair simulation execution unit 3 are completed, the target selection unit 60 refers to the repair cost database 65 and specifies a repair plan creation instruction that specifies one specification of one repair item. This is given to the creation unit 50.

The renovation plan creation unit 50 requests the model setting unit 40 of the renovation simulation execution unit 3 to set the corresponding building model in response to the renovation plan creation instruction, and thus uses the building model set by the model setting unit 40. Then, a temporal change in room temperature and humidity is calculated when the repair plan for repairing the relevant part of the target building at that time to the specification of the repair item specified in the repair plan creation instruction is executed.

Specifically, the renovation plan creation unit 50 includes a difference calculation unit 53, a signal conversion unit 52, and a separated signal correction unit 54 as shown in FIG. For example, when the renovation item specified in the renovation plan creation instruction is “insulation material” and the specification is “material A”, the refurbishment plan creation unit 50 reads the external data from the decomposition signal database 15 (FIG. 1). Thermal insulation characteristics of building of specific process signal obtained in renovation simulation when process model S20 of temperature measurement value and building model corresponding to renovation item and specification specified in renovation plan creation instruction are set in conversion unit 30 Temperature change component (hereinafter referred to as adiabatic origin component of the specific process signal) S10A, and the difference calculation unit 53 calculates the difference between them. Then, the difference between the external temperature and the room temperature calculated by the difference calculation unit 53 is given to the signal conversion unit 52.

At this time, in the signal conversion unit 52, the building model corresponding to the specification of the repair item specified in the repair plan creation instruction is set by the model setting unit 40 of the repair simulation execution unit 3 as described above. Thus, the signal conversion unit 52 uses this building model to time the temperature difference between the external temperature and the room temperature when the relevant part of the target building is repaired to the specification of the repair item specified in the repair plan creation instruction. A converted signal representing a target change is generated and output to the separated signal correction unit 54.

The separation signal correction unit 54 corrects the adiabatic component S10A derived from the specific process signal by adding the converted signal given from the signal conversion unit 52 to the adiabatic component S10A derived from the specific process signal read from the decomposition signal database 15. To do. As a result, a signal (hereinafter referred to as a renovation simulation signal) S21 representing a temporal change in room temperature when the relevant part of the target building is renovated to the specification of the renovation item specified in the renovation plan creation instruction is obtained. It will be.

In addition, the refurbishment plan creation unit 50 performs a renovation simulation that represents a temporal change in humidity in the building when the relevant part of the target building is renovated to the specification of the refurbishment item specified in the renovation plan creation instruction in the same manner as described above. The signal S21 is also calculated.

Then, the renovation plan creation unit 50 calculates the necessary air-conditioning fuel cost and the indoor comfort based on the room temperature and humidity renovation simulation signal S21 calculated in this way. At the same time, the repair plan creation unit 50 also calculates the man-hours and the total cost when the relevant part of the target building is repaired to the specification of the repair item specified in the repair plan creation instruction.

The renovation plan creation unit 50 executes the above processing every time a renovation plan creation instruction is given from the target selection unit 60. Then, the target selection unit 60 changes the repair items specified in the repair plan creation instruction and the specifications for one scenario, and sequentially changes the repair plan creation instructions that specify all the specifications of all the repair items. 50 is given sequentially. As a result, in accordance with these renovation plan creation instructions, the rehabilitation plan creation unit 50 executes the rehabilitation plan for refurbishing the relevant part of the target building to the specification of the renovation item specified in the renovation plan creation instruction, and The total cost, the comfort of the building in the case of the refurbishment, and the subsequent air-conditioning fuel cost are calculated.

Also, the target selection unit 60 and the renovation plan creation unit 50 perform the same processing for other scenarios. As a result, in the renovation plan creation unit 50, the number of man-hours and the total cost when the renovation plan for refurbishing the relevant part of the target building to the specification of each renovation item specified in the renovation cost database, and the renovation are performed. If so, the comfort of the building and the subsequent air fuel costs are calculated.

Then, after completing such a process, the renovation plan creation unit 50 calculates the man-hours and the total cost, the comfort of the building when the renovation is performed, and the air-conditioning fuel cost thereafter. For example, a repair plan 200 as shown in FIG. 4 in which the repair plans are arranged in descending order of comfort or in order of lower air-conditioning fuel costs is created and printed out or displayed on a screen.

In the case of the present embodiment, the repair cost database 65 corresponds to the scenario 25 for changing the resident behavior such as the number of times of opening and closing the windows and doors and the opening and closing time in addition to the specifications of the respective repair items. The repair simulation conditions (such as the number of times of opening and closing windows and doors and the opening / closing time) defined in the above are also stored as repair items.

Then, the target selecting unit 60, for such a scenario 25, as a modification plan creation instruction described above, a modification plan in which the condition of the modification simulation specified in the scenario 25 and one specification of one modification item are specified. A creation instruction is given to the repair plan creation unit 50.

When such a renovation plan creation instruction is given, the renovation plan creation unit 50 sets the setting of the building model corresponding to the specification of the refurbishment item specified in the renovation plan creation instruction to the model setting unit of the renovation simulation execution unit 3 40 (FIG. 1), and using the building model set by the model setting unit 40, the relevant part of the target building at that time is repaired to the specification of the repair item specified in the repair plan creation instruction. Calculate the change in room temperature and humidity over time when the renovation plan is executed.

Specifically, as shown in FIG. 6, the renovation plan creation unit 50, for example, the condition of the renovation simulation specified in the renovation plan creation instruction is “door opening / closing frequency and opening / closing time”, and the renovation plan creation instruction If the refurbishment item and specification specified in step 1 are “insulation material specifications”, an event signal S160 of “door opening / closing time and opening time” from the decomposition signal database 15 (FIG. 1) and a renovation plan creation The adiabatic origin component S10A of the specific process signal obtained in the repair simulation when the building model corresponding to the repair item and specification specified in the instruction is set in the conversion unit 30 (FIG. 1) is read out.

The refurbishment plan creation unit 50 differentiates the “door opening / closing times and opening / closing time” event signal S160 read from the decomposition signal database 15 by the difference calculation unit 53 and then sets the building model set in the signal conversion unit 52. Is converted into an event signal (conversion event signal) S161 having the same physical unit as the adiabatic component S160 of the specific process signal.

After that, the refurbishment plan creation unit 50 reads the event signal (conversion event signal) S161 from the decomposition signal database 15 as described above in the separation signal correction unit 54, and the renovation plan specified in the renovation plan creation instruction. The component derived from the heat insulation of the specific process signal is corrected by adding to the heat insulation derived component S10A of the specific process signal obtained in the renovation simulation when the building model corresponding to the item and specification is set in the conversion unit 30. As a result, the relevant part of the target building is renovated to the specification of the renovation item specified in the renovation plan creation instruction, and according to the contents of the “update of the number of times of opening and closing and opening and closing time” designated in the renovation plan creation instruction A repair simulation signal S21 representing a temporal change in room temperature when the door is opened and closed with the number of times of opening and closing and the opening and closing time after the update is obtained.

In addition, the repair plan creation unit 50 repairs the corresponding part of the target building to the specification of the repair item specified in the repair plan creation instruction in the same manner as described above, and the “opening and closing times” specified in the repair plan creation instruction. And a renewal simulation signal S21 representing a temporal change in humidity in the building when the door is opened and closed with the number of times of opening and closing and the opening and closing time after updating in accordance with the content of "update of opening and closing time".

Then, the renovation plan creation unit 50 calculates the air conditioning fuel cost for performing the necessary air conditioning control and the indoor comfort based on the room temperature and humidity renovation simulation signal S21 calculated in this way.

The refurbishment plan creation unit 50 executes the above process every time the renovation plan creation instruction is given from the target selection unit 60. Then, the target selection unit 60 changes the repair items specified in the repair plan creation instruction and the specifications of the scenario, and sequentially changes the repair plan creation instructions that specify all the specifications of all the repair items. Sequentially. As a result, in accordance with these renovation plan creation instructions, the refurbishment plan creation unit 50 executes the renovation plan for refurbishing the relevant part of the target building to the specification of the renovation item specified in the renovation plan creation instruction, and The comfort of the building and the subsequent air-conditioning fuel cost when the door is opened and closed with the number of times of opening and closing and the opening and closing time after updating according to the content of “Number of times of opening and closing and opening and closing time” specified in the plan creation instruction Each will be calculated.

Then, after completing such a process, the renovation plan creation unit 50 determines the refurbishment plan in which the comfort of the building and the subsequent air-conditioning fuel cost are obtained by the above calculation in the order of higher comfort or the subsequent air-conditioning fuel cost. The repair plans 200 arranged in ascending order are created and printed out or displayed on the screen.

(1-3) Structure of Various Data and Signals in Building Air Conditioning Improvement Support Service System FIG. 7 shows an example of the structure of various data and signals in the building air conditioning improvement support service system 1. In the building air-conditioning improvement support service system 1 according to the present embodiment, the modification plan 200 is output data based on scenario data. As described above, the building data 100 is data including information such as the building style, total floor area, floor plan, and resident population of the target building at that time. Each of these data and each signal also changes the relationship between the databases to 1: 1 or 1: n depending on whether the target building or the analysis target is room temperature or humidity.

(1-4) Process Flow for Building Air Conditioning Improvement Support Function FIG. 8 shows a flow of a series of processes executed in relation to the building air conditioning improvement support function described above in the building air conditioning improvement support service system 1.

In the building air-conditioning improvement support service system 1, one scenario 25 is first selected (SP 1), and thereafter, the scenario 25 out of process signals and event signals given to the scenario setting unit 20 of the scenario setting processing unit 2 is selected. Scenario data is added to the corresponding process signal or event signal (SP2).

Subsequently, in the conversion unit 30 of the remodeling simulation execution unit 3, the event signal and a part of the process signal are converted into a signal having the same physical unit as the specific process signal and given to the decomposition unit 10 (SP3). The specific process signal is decomposed into components for each variation occurrence factor in the unit 10 (SP4). Then, the components for each variation occurrence factor of the specific process signal obtained in this way are stored in the decomposition signal database 15 (SP5).

If the above-described repair simulation has not been executed for all specifications of all the repair items registered in the repair cost database 65 (SP6: NO), the same repair simulation is executed for each specification of the remaining repair items. Is done.

In the case where the repair simulation for all the specifications of all the repair items registered in the repair cost database 65 is completed (SP6: YES), the processing from step SP2 to step SP5 is executed for all scenarios 25. If not (SP7: NO), the same process is repeated for each scenario 25.

Eventually, when the processing of steps SP2 to SP5 is completed for all scenarios 25 (SP7: YES), one scenario 25 is selected by the target selection unit 60 of the modification plan creation processing unit 4 (SP8), and the scenario Under 25, the time change such as room temperature when executing the repair plan to repair the relevant part of the target building to one specification of one repair item registered in the repair cost database 65 creates the repair plan Derived by the unit 50 (SP9). Thereafter, the air conditioning fuel cost and the comfort of the subsequent building when such a renovation is performed are sequentially calculated by the renovation plan preparation unit 50 (SP10, SP11).

When the processing in steps SP9 to SP11 is not executed for all specifications of all the repair items registered in the repair cost database 65 (SP12: NO), the same applies to the specifications of the remaining repair items. The process is executed.

When the processing of steps SP9 to SP11 is completed for all the specifications of all the repair items registered in the repair cost database 65, the repair plan creation unit 50 performs the subsequent air conditioning fuel cost and comfort as described above. The respective renovation plans that have been calculated are ranked in descending order of comfort or in descending order of air-conditioning fuel costs (SP13).

If the processes in steps SP8 to SP13 are not executed for all scenarios 25 (SP14: YES), the same process is repeated for each scenario 25.

Then, after the execution of the processing from step SP9 to step SP13 for all scenarios 25 is completed, the modification plan creation unit creates a modification plan 200 for each scenario 25 and outputs it (SP15).

FIG. 9 is a flowchart showing specific processing contents of the disassembling process executed by the disassembling unit 10 in step SP4 of FIG. In the present embodiment, the independent component analysis method is applied as described above as a signal decomposition method for decomposing a specific process signal to be analyzed.

In the case of the present embodiment, the observation data in the independent component analysis method is a process signal and an event signal, and the number of these process signals and event signals input to the decomposition unit 10 is the number of independent components. As an objective function that satisfies independence, a minimization problem of a high-order cumulant derived from a high-order moment as a statistic may be applied. The fourth order is sufficient as a high-order cumulant, and the algorithm required in practical calculation time is, for example, Non-Patent Document 4 (A. Hyvarinen, J. Karhunen, E. Oja: Independent Component Analysis: John Wiley & Sons (2001)).

That is, when the matrix A that associates the observation signal SS (t) with the independent component signal S (t) is used,

The independent component analysis is to obtain this independent component signal, that is, the decomposed signal S (t). If all the decomposition signals S (t) that are so-called signal sources (sound sources) can be measured,

A matrix W that satisfies the above is uniquely obtained, but some observation signals SS (t) are mostly interfering, and independent measurement is difficult. For example, the independent component analysis shown in Non-Patent Document 4 solves this problem. In the present embodiment, a general technique shown in Non-Patent Document 4 or the like is used as a calculation procedure for independent component analysis. These processing procedures will be described below.

First, the decomposition unit 10 inputs observation data and the number of independent components (SP20). In the case of the present embodiment, as described above, the observation data includes a process signal and an event signal. The number of independent components is equivalent to the number of decompositions at the time of decomposing room temperature, room humidity, etc. according to the change factors from these observation data. That is, when the room temperature change is decomposed into the outside air temperature, the boiler start / stop as the heat source, and the door opening / closing, the number of independent components is 3. The number of independent components is set in advance by the user.

Subsequently, the decomposition unit 10 decorrelates the observation data as data preprocessing for independent component analysis (SP21). The decorrelation means that the average value of observation data is 0 (zero), and can be obtained by principal component analysis, which is one of multivariate analysis techniques. 9 is equivalent to making the average value of the observed data zero by principal component analysis.

Next, the decomposition unit 10 sets an objective function for independent component analysis (SP22), and thereafter calculates the independent component (SP23). The observation data was converted to time-series data with an average value of zero by the above-described decorrelation. Based on this characteristic, it is shown in Non-Patent Document 4 that an independent component for observation data can be obtained by minimizing the feature quantity of statistical data called cumulant, and is widely known as an algorithm called FastICA. Here, the cumulant is derived from the statistic moment. For example, the first-order cumulant is the average value of the observed data, the second-order cumulant is the variance representing the variation of the observed data, and the third-order cumulant is the third-order cumulant. Corresponds to the moment. Non-Patent Document 4 shows a method of obtaining an independent component by solving the problem of minimizing such a high-order cumulant, and can be obtained in a practical calculation time.

Through the above processing, the components for each factor of fluctuation of the specific process signal are obtained. Then, the decomposing unit 10 stores the components for each variation occurrence factor of the specific process signal thus obtained in the decomposing signal database in step SP5 of FIG.

(1-5) Specific Configuration Example of Building Air Conditioning Improvement Support Service System According to the Present Embodiment FIG. 10 shows a specific configuration example of the building air conditioning improvement support service system 1 according to the present embodiment. FIG. 10 is a configuration example when the building air conditioning improvement support service system 1 is applied to HEMS. Only the function of the disassembling unit 10 (FIG. 1) is given to the cloud server 11, and the scenario setting unit 20 and the model parameter calculating unit 44. The functions of the model setting unit 40, the conversion unit 30, the target selection unit 60, and the renovation plan creation unit 50 are provided to a general HEMS 111 that manages and manages the HEMS. In FIG. 10, weather data and the like are given to the overall HEMS 111 via the network 112 as a partial scenario 25.

The cloud server 110 is a general-purpose server device having a CPU (Central Processing Unit) and information processing resources such as a memory, and the CPU executes a program stored in the memory, whereby the building air conditioning improvement support service system 1 is decomposed. The function as the part 10 is demonstrated. The overall HEMS 111 is also configured to include information processing resources such as a CPU and a memory, and the CPU executes a program stored in the memory, so that the scenario setting unit 20 and the model parameter calculation unit of the building air conditioning improvement support service system 1 44, the model setting unit 40, the conversion unit 30, the target selection unit 60, and the modification plan creation unit 50 are exhibited.

In the building air conditioning improvement support service system 1, the room temperature and humidity in the building measured by the thermostat 113 and the thermometer (TRV) 114A mounted on the radiator 114 (FIG. 11) of each room in the building are provided. The temperature of the radiator 114 measured from time to time is supplied to the overall HEMS 111 as a process signal.

Also, the general HEMS 111 is notified of information about the open / closed state (open or closed) of the window or door detected by the sensor 115 installed on the window or door, and the state (on / off) from the heat source 117. Thus, the overall HEMS 111 generates, for example, an event signal indicating the number of times of opening / closing the window or door and the opening / closing time of the window or door detected by the sensor 115, and based on a notification from the heat source 117. Then, an event signal indicating on / off of the heat source 117 is generated.

Based on these process signals and event signals, the general HEMS 111 then sets the scenario setting unit 20, the model parameter calculation unit 44, the model setting unit 40, the conversion unit 30, the target selection unit 60, and the modification described above with reference to FIGS. Various processes related to the plan creation unit 50 are executed.

In the case of the example of FIG. 10, the decomposition signal database 15 is arranged on the cloud server 110 side as the function of the decomposition unit 10 is also provided on the cloud server 110 side, while the other model parameter database 45 and the repair cost database. 65 and the like are arranged on the overall HEMS 111 side.

FIG. 11 shows an example in which the building air-conditioning improvement support service system 1 according to the present embodiment is applied to central heating in the configuration of FIG. The overall HEMS 111 is preliminarily provided with a heat insulation characteristic for each room as a model, and the overall HEMS 111 performs optimal control of air conditioning for each room based on these models. In this way, by collectively controlling the thermometer (TRV) 114A of the radiator 114 in each room, it is possible to take into account the interference of room temperature changes between the rooms, and so-called air-conditioning zoning control can be performed. Although FIG. 11 shows an example in which the sensor 115 is installed in a window or a door, the air-conditioning zoning control can also be performed by installing the human sensor 116 in each room.

(1-6) Effects of the present embodiment As described above, in the building air conditioning improvement support service system 1 of the present embodiment, a specific process signal fluctuates when a predetermined modification item of a building is modified to a predetermined specification. A repair simulation for obtaining a component for each factor is executed for each specification of each repair item, and a repair plan 200 is created based on the simulation results of these repair simulations. At this time, the building space improvement support service system 1 obtains a component for each variation occurrence factor of the process signal in which the variation component of the process signal due to the resident behavior is excluded in the repair simulation.

Therefore, according to the building air-conditioning improvement support service system 1, it is possible to provide an optimal renovation plan 200 (improvement method) that also considers resident behavior for improving the comfort of the building space.

(2) Second Embodiment Next, a building air conditioning improvement support service system according to a second embodiment will be described below with reference to FIGS. In the building air conditioning improvement support service system, process signals and event signals are input and scenario data is added. This scenario is, for example, door opening / closing, boiler ON / OFF, weather condition change, and the like. For the event signal and part of the process signal, the conversion unit 30 converts the signal into the same unit system as the process signal using the model parameter. In other words, the disassembling unit 10 sets the physical units as input information. The output of the decomposition unit 10 is temporarily stored in the decomposition signal database 15. The processing so far is the same as in FIG. Next, using the decomposition data storage result, the control parameters registered in the control parameter database 85 are compared for each scenario, adjusted by the control parameter adjusting unit 80, and the optimum parameter determined by the control parameter determining unit 70. . At this time, a control parameter based on the model characteristics is derived from the model setting unit 40 by referring to the model parameter used in the control parameter adjustment. The derivation calculation procedure is based on, for example, Generic Model Control shown in Non-Patent Document 5 (Suzuki, et al .: Application of Generic Model Control to batch polymerization temperature control: SCEJ 70th Annual Meeting). It is possible to derive a proportional gain and an integral gain as control parameters.

As an objective function 86 for deriving this control law,

Apply. In Expression (5), y is a control signal, that is, room temperature, r is a target value, and k1 and k2 can be associated with a proportional gain and an integral gain. In order to optimally control the room temperature, an objective function can be defined such as minimizing dy / dt. The control parameters are registered as a parameter list 300 and are installed in each BEMS and HEMS controller. For example, room temperature control is applied to the control parameters of thermostat control.

FIG. 15 is a flowchart showing the flow of processing in the building air conditioning improvement support service system according to this embodiment. Control parameter adjustment and objective function calculation are as described above. Note that, when the processing is executed online, the model data update determination is omitted, and the procedure up to the control parameter may be repeated every control cycle as time progresses.

Next, an example of control target value generation support in the building air conditioning improvement support service system of the present embodiment will be described below with reference to FIGS. The control target value generation is to correct a control target value that has been set to a constant value based on the decomposition result. Of the process signal S10 and the decomposition result, the process drive data is compared and the control parameter is set. Specifically, instead of correcting the control target value itself, the target to be compared with the control target value is compared with the observation signal S10 and the decomposition signal S150 to derive the corrected control value Sr10. The corrected control value r10 eliminates a disturbance factor that deteriorates the performance of Fordback control, and realizes stable automatic control. For example, even if a change in room temperature due to opening and closing of the window occurs in a short time, the fuel consumption is suppressed by suppressing the heat source control. In this case, since the opening and closing of the window is a short period, a temperature decrease can be suppressed by the inherent heat insulation performance of the building, and a decrease in comfort can also be suppressed.

FIG. 18 is a flowchart showing a processing procedure of control parameter adjustment support processing in the building air conditioning improvement support service system according to this embodiment. The comparison of the decomposition signal and the control amount and the generation of the control target value are as described above. Note that, when the processing is executed online, the model data update determination is omitted, and the procedure up to the control parameter may be repeated every control cycle as time progresses.

Next, one example of the model parameter update in the building air conditioning improvement support service system of the second embodiment will be described below with reference to FIG. The model setting unit 40 compares the process signal S10 with the addition of the decomposition signal, confirms the decomposition accuracy, and determines the probability of the model used for unifying the physical unit of the decomposition input. In other words, if the temperature change derived from insulation is too large, the gain of the model parameter corresponding to the event signal is increased, and conversely, if the temperature change derived from insulation is too small, the insulation data is considered too large and the building data is reviewed. Judging. These processes are ruled and provided in the model setting unit 40.

FIG. 20 shows an example of the data structure related to control parameter adjustment in the building air conditioning improvement support service system according to the present embodiment. In the present embodiment, the data structure is based on scenario data, and the control parameter 300 is output data. Further, the building data 100 is data including the floor plan of the building to be controlled and the resident characteristics. The relationship between the databases changes to 1: 1 or 1: n depending on the building to be controlled or whether the signal to be decomposed is room temperature or another signal. The control parameter 300 is assumed to be connected to an automatic control system, and is implemented as a parameter of a BEMS or HEMS controller, for example.

An example of signal decomposition in the building air conditioning improvement support service system according to the present embodiment will be described below with reference to FIG. Since the room temperature measurement value S10 is an object to be decomposed, the physical unit is unified at the temperature ° C. It is assumed that the room temperature measurement values shown in FIG. 21 include those due to solar radiation or outside air temperature changes and temperature changes associated with window opening / closing and heating control. According to the scenario setting, the window opening / closing signal and the heating on / off control signal are converted into a temperature signal, and signal separation is performed in the disassembling unit 10, so that one process drive signal and two event drive signals shown in the right diagram of FIG. Decompose. In the support service method of the present invention, the temperature change due to the heat insulation characteristics of the building, the temperature disturbance accompanying the resident behavior such as windows and doors, and the influence factors of the air conditioning control that operates in response thereto are decomposed and the results are utilized.

FIG. 22 shows an example of signal decomposition in the building air-conditioning improvement support service system according to the present embodiment when the control target value is corrected using the decomposition result. The left figure shows the conventional control characteristics to which the method of the present invention is not applied. The boiler control is executed by detecting the temperature disturbance accompanying the opening and closing of the window. On the other hand, the right figure shows the result of the control target value correction of the present invention. By comparing the room temperature change derived from insulation with the room temperature setting value indicated by the dotted line, boiler activation due to the effect of temporary room temperature drop due to window opening and closing To suppress fuel consumption. Moreover, it is the result of suppressing the room temperature rise by boiler control.

FIG. 23 shows an example of the repair plan support in the building air conditioning improvement support service system according to this embodiment. Prepare a model with gain and time constant as model parameters. The gain and time constant are uniquely determined from the heat insulation characteristics, heat source dose, window characteristics, and the like defined by the building data. After preparing a finite number of these model characteristics from “Model0” to “Model2”, the comparison calculation is executed to derive the renovation plans “PlanA”, “PlanB”, and “PlanC”. By associating model data with each other at the time of derivation, it becomes possible to search when updating the model separately. Record the evaluation items related to the modification of the building body instead of automatic control, such as heat insulation material, construction area, and man-hours, and list the associated fuel costs, comfort, and total costs. Then, the optimal repair plan is selected from the comparison between the repair plans. In this case, the user can select items to be prioritized such as remodeling man-hours, total cost, or comfort.

FIG. 24 shows another example of the repair plan support in the building air conditioning improvement support service system according to this embodiment. Prepare a model with gain and time constant as model parameters. The gain and time constant are uniquely determined from the heat insulation characteristics, heat source dose, window characteristics, and the like defined by the building data. After preparing a finite number of these model characteristics from “Model0” to “Model2”, the comparison calculation is executed to derive the renovation plans “PlanA”, “PlanB”, and “PlanC”. By associating model data with each other at the time of derivation, it becomes possible to search when updating the model separately. Record the evaluation items related to the modification of the building body instead of automatic control, such as heat insulation material, construction area, and man-hours, and list the associated fuel costs, comfort, and total costs. Furthermore, in this embodiment, ventilation items and hygiene items are added. The ventilation item can be set separately from the scenario item. Here, the presence / absence of the ventilation function or the ventilation amount is described as a modified item. For the hygiene item, for example, the condition for generating mold is used as an evaluation item, and a rule for determining the possibility of mold generation from a change in temperature and humidity in the room is included in the comparison process. The ventilation function is considered as a so-called dehumidification function, and it is possible to derive the absolute humidity from the humidity signal measured as the process signal and estimate the humidity reduction effect by the ventilation capacity. As for the ventilation item, it is necessary to consider the operation of opening and closing the window, but here it is assumed that ventilation functions as exhausting absolute humidity.

FIG. 25 shows an example of the cloud function decomposition unit 10 when the building air-conditioning improvement support service system according to this embodiment is applied to central heating. For the signal separation, the processing flow is shown in FIG. 9, but in FIG. 25, room temperature is applied to the inputs of the heat insulation model, the door opening / closing model, the window opening / closing model, and the heat source control model. This is because it can be applied to model parameters that change according to room temperature, and by adding this input, it is possible to eliminate the need to execute a scenario change each time the model parameters are corrected.

The first and second embodiments of the present invention have been described above with reference to FIGS. The measurement signal decomposition process enables building repair plans to control parameter adjustments. When the calculation load is high, the decomposition process is realized as a cloud, thereby reducing the cost and realizing the functions of BEMS and HEMS alone.

(3) Other Embodiments In the first and second embodiments described above, the logical configuration of the building air conditioning improvement support service system is configured as shown in FIG. 1 or FIG. 10 and FIG. 11 have been described. However, the present invention is not limited to this, and various other configurations can be widely applied.

The present invention can be widely applied to a building air conditioning improvement support service system that supports building improvement.

DESCRIPTION OF SYMBOLS 1 ... Building air-conditioning improvement support service system, 2 ... Scenario setting process part, 3 ... Renovation simulation execution part, 4 ... Renovation plan preparation process part, 10 ... Decomposition part, 15 ... Decomposition signal database, 20 ... ... scenario setting unit, 25 ... scenario, 30 ... conversion unit, 40 ... model setting unit, 44 ... model parameter calculation unit, 45 ... model parameter database, 45D ... model parameter, 50 ... creation of renovation plan Department, 60 ... target selection department, 65 ... repair cost database, 100 ... building data, 200 ... repair plan.

Claims

In the building air conditioning improvement support service system that provides the building air conditioning improvement support service,
A process signal that is environmental data that affects the comfort of the building space of the building and an event signal that is information related to resident behavior are input. Based on the input process signal and the event signal, a predetermined signal of the building is input. A repair simulation execution unit that executes a repair simulation for obtaining a component for each variation occurrence factor of the process signal when the repair item is repaired to a predetermined specification, for each of the specifications of the plurality of predetermined repair items;
Based on the simulation result of each of the renovation simulations, a change in the environmental data of the building when the predetermined renovation item of the building is changed to the predetermined specification is obtained for each of the specifications of each renovation item. The evaluation value for each specification of each renovation item is calculated based on the obtained change in the environmental data, and the building renovation plan is created based on the calculated evaluation value for each specification of each renovation item And a renovation plan creation department
The repair simulation execution unit
The building air-conditioning improvement support service system characterized in that, in the renovation simulation, a component for each variation occurrence factor of the process signal excluding a variation component of the process signal due to resident behavior is obtained.
The environmental data is
The building improvement support service system according to claim 1, wherein the building improvement support service system is a measurement value of room temperature and humidity in the building.
The repair simulation execution unit
The building improvement support service system according to claim 2, wherein the process signal is decomposed by an independent component analysis method to obtain a component for each factor of fluctuation of the process signal.
Provided in the previous stage of the renovation simulation execution unit, comprising a scenario setting processing unit that processes the process signal or event signal corresponding to a scenario that is a predetermined condition of the renovation simulation,
The repair simulation execution unit
The repair simulation for each of the specifications of each of the repair items is executed for each scenario,
The repair plan creation processing unit
The building air conditioning improvement support service system according to claim 1, wherein the renovation plan is created for each scenario.
In the building air-conditioning improvement support service method executed by the building air-conditioning improvement support service system that provides the building air-conditioning improvement support service,
A process signal that is environmental data that affects the comfort of the building space of the building and an event signal that is information related to resident behavior are input. Based on the input process signal and the event signal, a predetermined signal of the building is input. A first step of executing, for each of the specifications of a plurality of predetermined repair items, a repair simulation for obtaining a component for each variation occurrence factor of the process signal when the repair item is repaired to a predetermined specification;
Based on the simulation result of each of the renovation simulations, a change in the environmental data of the building when the predetermined renovation item of the building is changed to the predetermined specification is obtained for each of the specifications of each renovation item. The evaluation value for each specification of each renovation item is calculated based on the obtained change in the environmental data, and the building renovation plan is created based on the calculated evaluation value for each specification of each renovation item And a second step of
In the first step,
The building air-conditioning improvement support service method characterized in that, in the repair simulation, a component for each variation occurrence factor of the process signal is obtained by excluding a variation component of the process signal due to resident behavior.
The environmental data is
The building improvement support service method according to claim 5, wherein the building improvement support service method is a measurement value of room temperature and humidity in the building.
In the first step,
The building improvement support service method according to claim 6, wherein the process signal is decomposed by an independent component analysis method to obtain a component for each factor of fluctuation of the process signal.
A scenario setting processing step that is executed before the first step and processes the process signal or event signal corresponding to a scenario that is a predetermined condition of the repair simulation;
In the first step,
The repair simulation for each of the specifications of each of the repair items is executed for each scenario,
In the second step,
6. The building air-conditioning improvement support service method according to claim 5, wherein the repair plan is created for each scenario.