JP2016066363A - Energy diagnosis system and energy diagnosis program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a technology for presenting information related to energy requested by a client.SOLUTION: An energy diagnosis system 100 includes: a storage device 101; and an arithmetic unit 103 for executing the tenth processing to fifth processing, and for calculating the energy consumption estimated amount of selected energy equipment for each of a plurality of patterns, and for calculating fee data of each of the plurality of patterns by applying the energy consumption estimated amount of each type of energy to a selected fee plan, and for determining a predetermined plan from the plurality of patterns on the basis of the calculated fee data, and for transmitting the determined predetermined plan to the terminal of a client.SELECTED DRAWING: Figure 4

Description

  The present invention relates to an energy diagnostic system and an energy diagnostic program.

  In companies and households, various devices are operated using energy such as electricity and gas. These energies are provided according to various price plans set by electric power companies and gas companies.

  When deciding on a price plan, access the power company's or gas company's website from the terminal owned by the customer, and ask a simple question (information about the current price plan, morning, night type, time to do housework, etc. There is a service that suggests a recommended price plan simply by responding to the energy usage.

  “Choice menus that can be selected Easy diagnosis!”, [Online], Tokyo Electric Power Co., Inc. [Search April 22, 2014], Internet <URL: http: // www. tepco. co. jp / e-rates / individual / menu / home / index-j. html>   "Optimum price menu diagnosis service", [online], Tokyo Gas Co., Ltd., [April 22, 2014 search], Internet <URL: http: // e-com. Tokyo-gas. co. jp / saitekki / bestmenu. aspx>

  Here, each consumer has a desire to grasp his or her own energy usage status (for example, usage status for each device) or to determine a rate plan for each energy that is more suitable for him.

  The objective of this invention is providing the technique which can show the information regarding the energy which a consumer desires.

  In order to solve the above problem, an energy diagnostic system according to a first aspect includes a storage device and an arithmetic device. The arithmetic device executes the tenth process to the fifteenth process. The tenth process is an energy that can be incorporated into a predetermined plan based on the device information including the type of energy device provided in the residence and the type of energy available in the residence, stored in the storage device. Select a rate plan for each type of equipment and energy. The eleventh process creates a plurality of patterns that combine the selected energy devices and rate plans. The twelfth process is based on the energy consumption estimated amount per unit time for each energy device obtained in advance and the coefficient preset for each energy device, and the energy devices selected for each of the plurality of patterns. Calculate the estimated energy consumption. In the thirteenth process, the energy consumption estimated amount for each energy type calculated in the twelfth process is applied to the selected rate plan to calculate rate data for each of the plurality of patterns. In the fourteenth process, a predetermined plan is determined from a plurality of patterns based on the calculated fee data. In the fifteenth process, the determined predetermined plan is transmitted to the customer terminal.

  Moreover, in order to solve the said subject, the energy diagnostic program which concerns on Claim 3 makes a computer perform the 10th process-15th process. The tenth process is an energy that can be incorporated into a predetermined plan based on the device information including the type of energy device provided in the residence and the type of energy available in the residence, stored in the storage device. Select a rate plan for each type of equipment and energy. The eleventh process creates a plurality of patterns that combine the selected energy devices and rate plans. The twelfth process is based on the energy consumption estimated amount per unit time for each energy device obtained in advance and the coefficient preset for each energy device, and the energy devices selected for each of the plurality of patterns. Calculate the estimated energy consumption. In the thirteenth process, the energy consumption estimated amount for each energy type calculated in the twelfth process is applied to the selected rate plan to calculate rate data for each of the plurality of patterns. In the fourteenth process, a predetermined plan is determined from a plurality of patterns based on the calculated fee data. In the fifteenth process, the determined predetermined plan is transmitted to the customer terminal.

  ADVANTAGE OF THE INVENTION According to this invention, the information regarding the energy which a consumer desires can be shown. Specifically, various plans including a charge plan for each energy can be presented to the consumer.

It is a network block diagram including the energy diagnostic system which concerns on 1st Embodiment. It is a figure which shows the residence which concerns on 1st Embodiment. It is a figure which shows the measuring device which concerns on 1st Embodiment. It is a figure which shows the energy diagnostic system which concerns on 1st Embodiment. It is a figure which shows the arithmetic processing apparatus which concerns on 1st Embodiment. It is a figure which supplements description of the process by the arithmetic processing apparatus which concerns on 1st Embodiment. It is a figure which supplements description of the process by the arithmetic processing apparatus which concerns on 1st Embodiment. It is a figure which supplements description of the process by the arithmetic processing apparatus which concerns on 1st Embodiment. It is a figure which supplements description of the process by the arithmetic processing apparatus which concerns on 1st Embodiment. It is a figure which supplements description of the process by the arithmetic processing apparatus which concerns on 1st Embodiment. It is a figure which supplements description of the process by the arithmetic processing apparatus which concerns on 1st Embodiment. It is a flowchart which shows the process by the arithmetic processing apparatus which concerns on 1st Embodiment. It is a figure which shows the arithmetic processing apparatus which concerns on 2nd Embodiment. It is a figure which supplements description of the process by the arithmetic processing apparatus which concerns on 2nd Embodiment. It is a flowchart which shows the process by the arithmetic processing apparatus which concerns on 2nd Embodiment.

<First Embodiment>

With reference to FIGS. 1-12, the energy diagnostic system 100 which concerns on 1st Embodiment is described. Note that “energy (energy type)” in the present embodiment indicates electricity and gas, but energy (energy type) is not limited thereto. For example, the case where kerosene or the like is included as energy is also included in the scope of the present invention.
[Outline of energy diagnosis system]

  FIG. 1 is a diagram illustrating a network configuration example including an energy diagnostic system 100 according to the present embodiment.

  The energy diagnosis system 100 is a computer system for providing consumers with energy usage status for each device (details will be described later).

  The customer's residence 200 generally has a plurality of locations (main rooms, other rooms, non-rooms (corridors), etc.), and energy devices 300 (energy devices 300 are arranged) in each location. There may be no place). The energy device 300 is a device that operates using electricity, gas, or the like as energy. The energy device 300 that operates using electricity as energy may be referred to as an “electric device”, and the energy device 300 that operates using gas as energy may be referred to as a “gas device”.

  FIG. 2 is a diagram illustrating an example of a residence 200 according to the present embodiment. The residence 200 has a main room A, other rooms B to D, and a non-room E. In the main room A, heating equipment, cooling equipment, and lighting equipment are arranged as the energy equipment 300. In the other room B, as the energy device 300, a heating device, a cooling device, and a lighting device are arranged. In the other room C, a hot water supply device is arranged as the energy device 300. In the other room D, a ventilation device is arranged as the energy device 300. In the non-residential room E, a lighting device is arranged as the energy device 300. The types of lighting equipment, cooling equipment, heating equipment, hot water supply equipment, and ventilation equipment are examples of “types of energy equipment”. The main living room A, the other living rooms B to D, and the non-living room E are examples of “a place where energy devices are arranged”.

  In addition, the measurement device 400 is provided in the residence 200. The measuring device 400 measures the consumption of energy actually used by the energy device 300 (actual measurement value). The measuring device 400 is provided for each type of energy. In this embodiment, a gas measuring device 400a and an electric measuring device 400b are provided. The measuring device 400 is, for example, a smart meter, a pulse meter, or the like. Alternatively, an energy management system such as a HEMS (Home Energy Management System) may be used as the measuring device 400.

  The measuring device 400 is connected to the energy diagnostic system 100 of the present embodiment via the network N so as to be communicable. The measuring device 400 can automatically transmit energy consumption data for each type of energy to the energy diagnostic system 100 every predetermined time.

  Here, a specific example relating to the arrangement of the measuring device 400 will be described. FIG. 3 is a diagram illustrating a specific configuration of the measuring device 400a according to the present embodiment. In general households, when hot water is supplied from a hot water supply device (energy device 300) to each facility (bathroom, sink, floor heating, etc.), the use of header pipe H has become the mainstream. One end of the header pipe H is connected to the hot water supply device. The header pipe H is connected to a plurality of sub-pipes S that provide hot water supplied from a hot water supply device to each facility in the residence. The measuring device 400a is provided at a connection portion between the header pipe H and the hot water supply device. Therefore, the measuring device 400a can measure the total amount of hot water supplied from the hot water supply device. The measuring device 400a can determine the consumption of gas used in the hot water supply device from the total amount of hot water supplied. By adopting such a configuration, it becomes possible to grasp the consumption amount of energy (gas) supplied to the dwelling 200 only by providing one measuring device.

  The terminal 500 is an information terminal owned by a customer located in the residence 200, and specifically, a mobile phone, a tablet terminal, a notebook PC, or the like can be assumed. The customer terminal 500 holds an application 510 as an application that cooperates with the energy diagnosis system 100, and can execute the application 510 to realize a necessary function.

  The energy company system 600 is a system owned by a company (gas company or power company) that provides each energy. The energy provider system 600 holds information about a contractor including a rate plan with which the residence 200 contracts.

  The energy diagnosis system 100 according to the present embodiment is connected to the terminal 500 owned by the consumer and the energy provider system 600 via the network N so as to be communicable.

[Details of energy diagnostic system]

  Next, with reference to FIG. 4, the specific structure of the energy diagnostic system 100 in this embodiment is demonstrated. The energy diagnosis system 100 includes a storage device 101, a memory 102, an arithmetic device 103, an input device 104, an output device 105, and a communication device 106. The energy diagnostic system 100 according to the present invention includes at least a storage device 101 and an arithmetic device 103.

  The storage device 101 is composed of an appropriate nonvolatile storage device such as a hard disk drive. The storage device 101 includes a program 110 for causing the arithmetic device 103 to execute a predetermined function, a customer database 111, a life log database 112, a calculation database 113, a device database 114, and a plan database 115.

  The memory 102 is configured by a volatile storage device such as a RAM. The arithmetic device 103 controls the energy diagnosis system 100 as a whole. The arithmetic device 103 functions as the first processing unit 110A to the ninth processing unit 110I by reading the program 110 in the present embodiment into the memory 102 and executing it (details will be described later), for example. The input device 104 accepts key input and voice input from the user. The output device 105 is a display or the like that displays processing data. The communication device 106 is connected to the network N and communicates with other devices such as the terminal 500 and the energy provider system 600. When data is exchanged only with the above-described other devices, the energy diagnostic system 100 may not include the input device 104 and the output device 105.

[Specific processing by energy diagnosis system]

Next, specific processing executed by the energy diagnostic system 100 will be described with reference to FIGS. As described above, the arithmetic device 103 functions as the first processing unit 110A to the ninth processing unit 110I by executing the program 110. Note that the example shown in FIG. 2 is referred to for the structure of the residence 200 (the main living room A and the like), the type of the energy device 300, and the like.
(First process)

  110 A of 1st process parts are the apparatus information containing the kind of energy apparatus 300 with which the residence 200 is equipped and the place where the said energy apparatus 300 is arrange | positioned memorize | stored in the memory | storage device 101, the heat insulation performance of the residence 200, and Based on the solar heat acquisition coefficient of the residence 200, the primary energy consumption for each device field of the energy device 300 is calculated.

  The equipment field of the energy equipment 300 is a classification of each equipment by function (heating, cooling, hot water supply, etc.). In the present embodiment, the equipment field includes a heating equipment field, a cooling equipment field, a hot water supply equipment field, a lighting equipment field, and a ventilation equipment field.

  The life log database 112 of the storage device 101 includes device information including the type of the energy device 300 provided in the residence 200 and the location where the energy device 300 is disposed, the heat insulation performance of the residence 200, and the solar heat acquisition coefficient of the residence 200. Is remembered. The life log database 112 stores a plurality of patterns in advance for device information, heat insulation performance, and solar heat acquisition coefficient.

  For example, the consumer activates the application 510 on the terminal 500 and accesses the energy diagnostic system 100. And a consumer inputs into a questionnaire item in the questionnaire screen displayed by the application 510. FIG. This item includes, for example, a personal ID for identifying a customer, a password for logging in to a personal page, a zip code, a housing type, a house age, a lifestyle information, information on energy equipment arranged in a residence, solar power generation Information, energy usage information (consumption, rate plan, past rate). The housing type is, for example, a structure (wooden structure, RC structure, steel structure), an apartment house or a detached house. The structure (two-story, one-story, basement, etc.), heading, floor plan, etc. ". The life style information is information for estimating a period during which the consumer uses the energy device. For example, the lifestyle information is information on the activity time of the consumer (morning, night type, whether they are at home on weekdays, etc.). .

  When the input of the item is completed, the arithmetic unit 103 stores the item in the customer database 111 and sends the information to the life log database 112. The computing device 103 uses the life log database 112 to store information (equipment information, insulation performance of the residence 200, and solar heat acquisition coefficient of the residence 200) corresponding to the input items (for example, zip code, housing type, and age of residence). Read from. The heat insulation performance of the residence 200 is read as, for example, the amount of skin heat loss per unit temperature difference, the heat insulation rate of the floor, and the presence or absence of heat insulation piping. The solar heat acquisition coefficient of the residence 200 is read as, for example, a cooling period (heating period) solar heat acquisition amount per unit solar radiation intensity. Other information that is read out according to the input items includes the floor area of the living room (main room and other rooms), the total floor area of the house, the use of ventilation, the use of heat storage, the floor heating installation Rate, piping system, faucet type, presence or absence of highly insulated bathtub. These other information is stored in the life log database 112. In addition, when apparatus information, the heat insulation performance of the residence 200, and the solar heat acquisition coefficient of the residence 200 are known in advance, the consumer may directly input the information from the terminal 500. The read (or directly input) device information, heat insulation performance, and solar heat acquisition coefficient are stored in the customer database 111. In addition, this value can be transmitted to the terminal 500 once, and a consumer can check the value or can operate the terminal 500 to correct it. The corrected device information and the like are transmitted from the terminal 500 to the energy diagnosis system 100 and stored in the customer database 111.

  The first processing unit 110A processes the read (or directly input) device information, the heat insulation performance of the dwelling 200, and the solar heat acquisition coefficient of the dwelling 200 with a predetermined algorithm. The primary energy consumption is calculated. FIG. 6 is a graph showing an example of primary energy consumption calculated for each device field. The vertical axis represents energy consumption (MJ).

  The algorithm used in the first processing unit 110A is a known algorithm (for example, “Energy Conservation Standard (January 2013) provided by the National Institute for Land and Infrastructure Management of the Ministry of Land, Infrastructure, Transport and Tourism”). Proclamation) and calculation methods (programs, etc.) in accordance with the notification of certification standards for low-carbon buildings (promulgated in December 2012) ”(hereinafter referred to as“ programs provided by the MLIT ”) (See Algorithm).

Note that the device information includes various types of information according to the algorithm to be used, in addition to the type and location of the energy device 300. For example, in the case of an air conditioning / heating device, information on the number of devices arranged is included. If it is a hot water supply device, it includes information such as the specifications of the water heater (only hot water supply, including floor heating), hot water supply capacity, the number of faucets, the type of faucet, and the presence or absence of a dishwasher. If it is a lighting device, it includes information on the number of devices arranged.
(Second process)

  The second processing unit 110B calculates the primary energy for each device field calculated by the device information, the heat insulation performance, the solar heat acquisition coefficient, and a predetermined constant set for each device field, which is stored in the storage device 101. Classify consumption by location.

  The predetermined constant is a value used for dividing the primary energy consumption calculated in the first process for each room. The predetermined constant is stored in the calculation database 113. For example, when the known algorithm shown in the first process is used, only a value obtained by adding up the primary energy consumption of all the rooms in the residence 200 can be obtained. Therefore, a predetermined constant is used to divide the primary energy consumption calculated in the first process for each room. The predetermined constant in this case is, for example, a value set based on the contents of a program provided by the MLIT.

The second processing unit 110B uses the device information, the heat insulation performance, the solar heat acquisition coefficient, and the predetermined constant, for example, executes the processing described in the program provided by the MLIT, and the first processing unit 110A The calculated primary energy consumption for each device field is classified for each location. FIG. 7 is a graph showing an example in which the primary energy consumption of the heating device is divided into the main room A and the other room B among the devices shown in FIG. 6. The vertical axis represents energy consumption (MJ).
(Third process)

  110C of 3rd process parts classify | categorize the primary energy consumption classified for every place with the kind of energy based on the kind of energy used for the energy equipment 300 memorize | stored in apparatus information and the memory | storage device 101. FIG. .

  The device database 114 of the storage device 101 stores what kind of energy is used for each type of energy device 300 (information indicating the type of energy) (for example, electric or floor heating for an air conditioner). Gas). 110 C of 3rd process parts operate | move with the energy which each energy apparatus 300 arrange | positioned at the residence 200 (residential room) of a consumer operates based on the information which shows the kind of energy memorize | stored in apparatus information and the apparatus database 114 Determine whether.

For example, from the device information, the third processing unit 110C determines that the type of the heating device in the main living room A is floor heating, and the energy used for floor heating from the information indicating the type of energy is gas. Judge. Then, the third processing unit 110C classifies the primary energy consumption of the heating device of the main living room A classified by the second processing unit 110B as being due to gas. 110 C of 3rd process parts perform the same process with respect to each energy apparatus 300 arrange | positioned in the residence 200. FIG. FIG. 8 is a graph showing a processing result in the third processing unit 110C. The vertical axis represents energy consumption (MJ). As shown in FIG. 8, it can classify | categorize with the energy (electricity and gas) to be used for every apparatus arrange | positioned in the residence 200. FIG.
(Fourth process)

  Based on the third processing result, the fourth processing unit 110D calculates the ratio of the primary energy consumption for each energy device for each energy type.

Specifically, the fourth processing unit 110D has each energy device that operates on electricity (gas) when the total primary energy consumption of electricity (gas) calculated by the third processing unit 110C is 100. A ratio of 300 primary energy consumption is calculated. FIG. 9 is a graph showing a processing result in the fourth processing unit 110D. The vertical axis represents the ratio (%) of primary energy consumption.
(Fifth process)

  The fifth processing unit 110 </ b> E is provided for an actual measured value of energy consumption for each type of energy input in advance, and other equipment that is stored in the storage device 101 and is included in the residence 200 and not included in the energy device. Based on the energy consumption for each type of energy used, an energy consumption estimation amount for each energy type is calculated.

  The actual measurement value is a specific measurement value obtained by the measurement device 400. Alternatively, the actual measurement value is an actual value of energy consumption used in a certain period (for example, January or one year) input by the customer via the terminal 500. This actual value can be grasped, for example, from the payment details of the electricity charge and the gas charge.

  Other equipment is equipment that operates on energy (lightning, gas, etc.) and is not included in the fields of heating, cooling, lighting, ventilation, and hot water supply (for example, refrigerator, stove, microwave oven, etc.) Say. The equipment included in the fields of heating, cooling, lighting, ventilation, and hot water supply are, for example, a duct type central air conditioner, room air conditioner, FF heating equipment, panel radiator, hot water floor heating, fan convector, electric heater type floor heating. , Electric heat storage type heater, duct type ventilation equipment, wall type ventilation equipment, ceiling lighting, independent lighting, foot lamp, gas water heater, oil water heater, heat pump / gas instantaneous type hot water heater, electric heater water heater, electricity Heat pump water heater, solar water heater, solar system water heater, cogeneration equipment. Among the devices that may be arranged in the residence 200, those that correspond to the energy device 300 and those that correspond to other facility devices are classified in advance. Whether a certain residence 200 is equipped with other equipment (or the type if equipped) is input in advance via the terminal 500. In the present embodiment, it is assumed that other equipment is provided in the residence 200.

  The measured values and other information related to the equipment are stored in the customer database 111. In addition, the type of energy used in other equipment and the predicted value of energy consumption are stored in advance in the equipment database 114 (for example, if a stove, [use gas: energy consumption is OO [m3 ] / Year]), this value is determined based on, for example, information provided by the energy company, a value published by the device manufacturer, a value obtained by installing a measuring device in a general household, and the like.

  The fifth processing unit 110 </ b> E calculates the total value of energy consumption used in the other facility devices based on the information on the other facility devices stored in the customer database 111 and the information stored in the device database 114. Can be sought. Note that the fifth processing unit 110E may apply a correction value based on the lifestyle information stored in the life log database 112 when obtaining the total value.

The fifth processing unit 110E calculates a total value (for example, Y [m3] / year) of gas consumption used in other equipment from a total of measured values (for example, X [m3] / year) of gas. By subtracting, the estimated amount of gas energy consumption (XY = Z [m3] / year) is calculated. Similarly, the fifth processing unit 110E determines the total value of electricity consumption (for example, y [kWh] / year) from the total of measured electricity values (for example, x [kWh] / year). By subtracting (year), an estimated energy consumption amount of gas (xy = z [kWh] / year) is calculated. FIG. 10 is a graph showing a processing result in the fifth processing unit 110E. FIG. 10A is a graph showing an estimated amount of energy consumption of electricity. The vertical axis represents consumption (kWh), and FIG. 10B is a graph showing the estimated energy consumption of gas. The vertical axis represents consumption (m3). In addition, as a range which calculates | requires each value, not only a year unit but the month unit etc. may be sufficient.
(Sixth process)

  The sixth processing unit 110F calculates an energy consumption estimation amount for each energy device for each energy type based on the energy consumption estimation amount and the calculated ratio.

For example, the sixth processing unit 110F uses the gas calculated by the fourth processing unit 110D for the estimated energy consumption (Z [m3] / year) of the gas calculated by the fifth processing unit 110E. (Z [m3] × 25%) can be obtained by multiplying the ratio (25%) of the energy consumption amount of the heating equipment that uses the gas. The sixth processing unit 110F performs this process for each device whose ratio is calculated by the fourth processing unit 110D. Thereby, the energy consumption estimated amount for every apparatus arrange | positioned in the residence 200 is known. FIG. 11 is a graph showing a processing result in the sixth processing unit 110F. (A) of FIG. 11 is a graph which shows the energy consumption estimated amount of electricity for every apparatus. The vertical axis represents the consumption (kWh). FIG. 11B is a graph showing an estimated amount of gas energy consumption for each device. The vertical axis represents consumption (m3).
(Seventh process)

  The seventh processing unit 110G is configured to calculate the estimated energy consumption per unit time for each energy device based on life style information that is input in advance and for estimating a period in which the consumer uses the energy device. Calculate the amount.

As described above, the lifestyle information is, for example, information related to a consumer's activity time (morning, night type, whether he / she is at home on weekdays). For example, the seventh processing unit 110G sets the annual energy consumption estimation amount of the air conditioner to 100%, and calculates the hourly energy consumption estimation amount from 1:00 on January 1 to 23:00 on December 31 as lifestyle information. By allocating based on, the amount per unit time of the estimated energy consumption of the air conditioner is calculated. For example, in the case of a home with a full-time housewife, the allocation based on the lifestyle information is such that the energy is used to some extent during the weekday. On the other hand, in the case of a household where no one lives in the daytime, the daytime energy is allocated so as not to be used.
(Eighth process)

  The eighth processing unit 110H applies the estimated energy consumption amount per unit time to the charge plan for each type of energy stored in the storage device 101 and contracted by the consumer with the energy provider. Calculate charge data for each predetermined period.

  In general, consumers who use gas and electricity each contract a predetermined rate plan with an energy company. Information on the billing plan under contract is input via the terminal 500 and stored in the plan database 115.

For example, the estimated electricity consumption per unit time of the heating equipment using electricity calculated by the seventh processing unit 110G is 1 [kWh], and the currently charged electricity rate plan is 20 yen per 1 [kWh]. In some cases, the eighth processing unit 110H calculates a fee (14,400 yen) for a predetermined period (for example, January (30 days)) of a heating appliance that uses electricity. The eighth processing unit 110H calculates a charge for a predetermined period for each energy device 300 arranged in the residence 200.
(9th process)

  The ninth processing unit 110 </ b> I transmits the calculated fee data to the customer terminal 500 via the communication device 106. The consumer can check the charge data sent to the terminal 500 through the website or application 510 provided by the energy diagnosis system 100. That is, the consumer can confirm the current energy usage status for each device by confirming the charge data.

  It should be noted that the fee data can be provided in various formats. For example, the ninth processing unit 110I transmits the charge data for a predetermined period for each device calculated by the eighth processing unit 110H as it is (in this case, the terminal 500 can check the charge data for each device). Alternatively, the ninth processing unit 110I may add the charge data for a predetermined period for each device calculated by the eighth processing unit 110H for each energy type and transmit the information (in this case, the terminal 500 can check the price data for each type of energy).

[Processing flow of energy diagnosis system]

Next, processing of the energy diagnostic system 100 according to the present embodiment will be described with reference to FIG. In the following example, it is assumed that the arithmetic device 103 reads and executes a predetermined program 110.

  A consumer who desires energy diagnosis activates the application 510 on the terminal 500 to access the energy diagnosis system 100, for example. And a consumer inputs about a predetermined item in the questionnaire screen displayed by the application 510 (S10).

  The arithmetic device 103 reads the device information corresponding to the input predetermined item, the heat insulation performance of the residence 200, and the solar heat acquisition coefficient of the residence 200 from the life log database 112. As the first processing, the arithmetic device 103 processes the device information, the heat insulation performance of the residence 200, and the solar heat acquisition coefficient of the residence 200 with a predetermined algorithm, thereby the energy device 300 disposed in the residence 200 of the consumer. The primary energy consumption for each device field is calculated (S11).

  As the second process, the arithmetic device 103 uses the device information, the heat insulation performance, the solar heat gain coefficient, and the device calculated in S11 based on the predetermined constant set in advance for each device field stored in the storage device 101. The primary energy consumption for each field is classified for each place of the residence 200 (S12).

  As a third process, the arithmetic device 103 calculates the primary energy consumption classified for each location in S12 based on the device information and the type of energy used in each energy device 300 stored in the storage device 101. Sort by energy type (S13).

  As the fourth process, the arithmetic device 103 calculates the ratio of the primary energy consumption of each energy device 300 for each type of energy based on the processing result of S13 (S14).

  As the fifth process, the arithmetic device 103 is a pre-measured actual value of energy consumption for each type of energy, and the other stored in the storage device 101 and included in the residence 200 and not included in the energy device. Based on the energy consumption for each energy type of the equipment, an energy consumption estimated amount for each energy type is calculated (S15).

  As a sixth process, the arithmetic device 103 calculates the estimated energy consumption of each energy device 300 for each type of energy based on the estimated energy consumption calculated in S15 and the ratio calculated in S14. (S16).

  As the seventh process, the arithmetic unit 103 calculates the energy consumption estimated amount for each energy device calculated in S16 based on the lifestyle information for estimating the period in which the consumer uses the energy device, which is input in advance. Is calculated per unit time (S17).

  As the eighth process, the computing device 103 stores the estimated energy consumption per unit time calculated in S17 in the storage device 101 for each type of energy with which the consumer contracts with the energy provider. Apply to the charge plan and calculate the charge data for a predetermined period for each energy device (S18).

  The computing device 103 transmits the calculated fee data to the customer terminal 500 as a ninth process (S19).

  As described above, according to the energy diagnostic system 100 according to the present embodiment, the usage status of energy can be provided to consumers as, for example, fee data for a predetermined period for each device. Based on this information, customers can search for new plans and work on energy savings.

  In addition, when transmitting charge data to the customer's terminal 500, the ninth processing unit 110I may transmit additional information together. The additional information is stored in advance in the customer database 111, for example. The additional information is, for example, information related to a charge plan that is most selected by a person who lives in a residence of a similar type as the customer who performed the energy diagnosis. The ninth processing unit 110I reads the rate plan based on the house type information input by the consumer, and transmits it to the terminal 500 together with the rate data.

  Further, when calculating the energy consumption estimation amount, the weather condition and the amount of power generated by the photovoltaic power generation unit may be taken into consideration.

  In this case, the residence 200 is provided with a solar power generation unit that generates power by sunlight. The weather data such as the presence / absence of the solar power generation unit, the amount of solar radiation that directly affects the amount of power generated by the solar power generation unit, and the temperature, humidity, and precipitation that affect the energy consumption in the residence 200 are, for example, via the terminal 500. Is input. The energy diagnosis system 100 (the arithmetic device 103) applies the weather data to a predetermined weather prediction algorithm (which may adopt an existing weather prediction program), for example, a short period such as one day or one week from the present time, and Information on weather prediction is obtained by making predictions of the amount of solar radiation, temperature, humidity, and precipitation for a long period such as one month and one year, and this is stored in the storage device 101. The meteorological data given to the above-mentioned meteorological prediction algorithm includes observation values for the most recent one week, statistical values related to observation values for the same month in the past one year and ten years, etc., and these observation values and statistical values are combined to generate a weather prediction algorithm. Shall be given to Note that the weather forecast information may be acquired not only when the weather data is applied to the weather forecast algorithm, but also information previously announced by the weather forecasting organization may be acquired from the server device of the relevant organization.

  The energy diagnosis system 100 applies the weather prediction information read from the storage device 101 and the power generation capability information of the photovoltaic power generation unit installed in the residence 200 to a predetermined power generation prediction algorithm. The expected power generation amount in the residence 200 until the future is calculated. Information on the power generation capacity of the photovoltaic power generation unit installed in the residence 200 is input via the terminal 500. Alternatively, based on the information on the presence / absence of the photovoltaic power generation unit input via the terminal 500, the energy diagnosis system 100 can determine whether the power generation capability information is stored in the storage device 101 (life log database 112) according to the performance of the unit. It is also possible to read out the value.

When performing the fifth process, the energy diagnostic system 100 (the arithmetic device 103) subtracts the predicted power generation amount from the actual measurement value of the energy consumption amount of the energy type (electric power) input in advance, thereby calculating the power generation amount. It is possible to calculate an estimated energy consumption amount (an estimated amount of energy received from an energy provider).
Second Embodiment

  Next, an energy diagnostic system 100 according to the second embodiment will be described with reference to FIGS. In the present embodiment, an example will be described in which a predetermined plan (optimization plan) including a charge plan is presented to a consumer. Note that detailed description of the same configuration as in the first embodiment is omitted.

[Specific processing by energy diagnosis system]

With reference to FIG. 13, a specific process executed by the energy diagnostic system 100 according to the present embodiment will be described. In the present embodiment, by executing the program 110 stored in the storage device 101 (the description of the program is different from that in the first embodiment), the arithmetic device 103 can change the tenth processing unit 110J to the fifteenth processing unit. It functions as 110O.
(Tenth process)

  The tenth processing unit 110J is incorporated into a predetermined plan based on the device information stored in the storage device 101, including the device information including the type of the energy device 300 provided in the residence 200, and the type of energy available in the residence 200. It is possible to select a price plan for each energy device 300 and energy type.

  The device information and the type of energy are stored in the customer database 111 for each customer. Those data stored in the customer database 111 in advance may be used, or data newly input when a predetermined plan creation instruction is given. The device information in the present embodiment includes at least the type of energy device 300 provided in the residence 200. In addition, the plan database 115 stores a plurality of rate plans provided by the electric power company and the gas company.

  Here, for example, it is assumed that a certain customer instructs the energy diagnostic system 100 via the terminal 500 to create a predetermined plan. In this case, the tenth processing unit 110J reads information corresponding to the customer from the customer database 111. Specifically, the tenth processing unit 110J includes the types of energy devices 300 (for example, air conditioners and water heaters) provided in the consumer's residence 200 and the types of energy that can be used in the residence 200 (for example, Gas, electricity). Then, the tenth processing unit 110J selects an energy device 300 that can be incorporated into a predetermined plan according to the type of the read energy device 300. In addition, the tenth processing unit 110J reads a rate plan corresponding to the type of energy from the plan database 115.

Note that the energy device 300 to be selected is not limited to the one actually provided in the residence 200. For example, when the energy device 300 applied to the read rate plan is not actually provided in the residence 200, the tenth processing unit 110J selects the energy device 300 as a device that can be incorporated into a predetermined plan. May be.
(Eleventh process)

  The eleventh processing unit 110K creates a plurality of patterns obtained by combining the energy device 300 and the charge plan selected in the tenth process.

For example, the gas device G1, the gas device G2, the electric device E1, and the electric device E2 are selected as the energy device 300, the electric plan EP1 and the electric plan EP2 are selected as the electricity rate plan, and the gas plan GP1 as the gas rate plan, Assume that the gas plan GP2 is selected. In this case, the eleventh processing unit 110K creates a pattern (Pattern 1 to Pattern 16; see FIG. 14) obtained from all these combinations.
(Twelfth process)

  The twelfth processing unit 110L is selected for each of a plurality of patterns based on an estimated energy consumption amount per unit time for each energy device and a coefficient set in advance for each energy device. An energy consumption estimation amount of the energy device 300 is calculated.

  As the estimated energy consumption per unit time of the energy device 300, for example, a value obtained by the processing of the first embodiment is stored in the customer database 111 in advance. Coefficients set in advance for each energy device are stored in the device database 114 in advance. This coefficient is determined based on, for example, information provided by an energy company, a published value of a device manufacturer, a value acquired by installing a measuring device in a general household, and the like.

For example, for pattern 1 in FIG. 14, the twelfth processing unit 110L multiplies the estimated energy consumption per unit time of the gas device G1 by a coefficient to calculate the estimated energy consumption EC1 of the gas device G1. Similarly, the twelfth processing unit 110L multiplies the energy consumption estimated amount per unit time of the electric device E1 by a coefficient to calculate the energy consumption estimated amount EC2 of the electric device E1. The twelfth processing unit 110L performs the same process on all the created patterns. When a plurality of energy devices 300 using the same energy are included in a certain pattern, the twelfth processing unit 110L adds up the calculated energy consumption estimation amounts. In the present embodiment, “calculating the energy consumption estimated amount of the energy device 300 for which the twelfth processing unit 110 </ b> L has been selected” includes adding the calculated values.
(13th process)

  The thirteenth processing unit 110M applies the estimated energy consumption amount for each energy type calculated in the twelfth processing to the selected rate plan, and calculates fee data for each of a plurality of patterns.

For example, for the pattern 1 in FIG. 14, the thirteenth processing unit 110M applies the gas rate plan GP1 to the energy consumption estimated amount EC1 of the gas appliance G1, and calculates rate data. Similarly, the thirteenth processing unit 110M applies the electricity rate plan EP1 to the energy consumption estimated amount EC1 of the electrical device E1, and calculates rate data. The thirteenth processing unit 110M performs the same processing for all the created patterns (fourteenth processing).

  The fourteenth processing unit 110N determines a predetermined plan from a plurality of patterns based on the fee data calculated in the thirteenth process.

The predetermined plan is determined based on a preset criterion in the fourteenth processing unit 110N. For example, the fourteenth processing unit 110N determines, as a predetermined plan, a pattern in which the accumulated cost (value input by the customer) is the lowest among the created patterns. The predetermined plan is not limited to one. For example, the fourteenth processing unit 110N may determine, as the predetermined plan, a pattern in which the accumulated cost is reduced and a pattern in which the energy consumption is minimized from among the created patterns.
(15th process)

  The fifteenth processing unit 110O transmits the predetermined plan determined in the fourteenth process to the customer terminal 500. The predetermined plan includes a combination of energy devices 300, a combination of charge plans, a primary energy consumption, a charge for each energy related to one year, a cumulative cost, and the like. The consumer can confirm a predetermined plan sent to the terminal 500 through the website or the application 510 provided by the energy diagnosis system 100. In addition, when a consumer instructs the registration of the transmitted predetermined plan via the terminal 500, the arithmetic device 103 stores the predetermined plan in the customer database 111.

[Processing flow of energy diagnosis system]

Next, processing of the energy diagnostic system 100 according to the present embodiment will be described with reference to FIG. In the following example, it is assumed that the arithmetic device 103 reads and executes a predetermined program 110.

  A consumer who desires to create a predetermined plan (for example, an optimal plan suitable for his / her residence 200) activates the application 510 on the terminal 500 and accesses the energy diagnosis system 100, for example. Then, the consumer gives an instruction to create a plan on the plan creation screen displayed by the application 510 (in this case, the desired accumulated cost calculation year or the like may be input) (S20).

  As a tenth process, the arithmetic device 103 performs predetermined processing based on device information including the type of the energy device 300 provided in the residence 200 and the type of energy that can be used in the residence 200, which is stored in the storage device 101. A charge plan for each energy device 300 and energy type that can be incorporated into the plan is selected (S21).

  As the eleventh process, the arithmetic device 103 creates a plurality of patterns combining the energy device 300 selected in S21 and the charge plan (S22).

  As the twelfth process, the arithmetic device 103 performs a plurality of patterns based on the estimated energy consumption per unit time of each energy device 300 and the coefficient preset in each energy device 300. In addition, an estimated energy consumption amount of the energy device 300 selected in S21 is calculated (S23).

  As a thirteenth process, the arithmetic device 103 applies the estimated energy consumption amount for each energy type calculated in S23 to the rate plan selected in S21, and calculates fee data for each of a plurality of patterns (S24). ).

  As the fourteenth process, the arithmetic device 103 determines a predetermined plan from a plurality of patterns based on the fee data calculated in S24 (S25).

  As the fifteenth process, the arithmetic device 103 transmits the predetermined plan determined in S25 to the customer terminal 500 (S26).

  Thus, according to the energy diagnostic system 100 according to the present embodiment, it is possible to present a plan (including a charge plan) according to the energy usage status to the consumer. Based on this information, the customer can examine a new rate plan and grasp the energy cost.

  Note that the arithmetic device 103 may execute a process of calculating the initial investment amount of the energy device 300 used for each of the created plurality of patterns for each of the plurality of patterns. The initial investment amount of each energy device 300 is stored in advance in the device database 114. In this case, the fifteenth processing unit 110O transmits the initial investment amount corresponding to the pattern determined as the predetermined plan to the terminal 500 together.

  In addition, the customer can make corrections to the transmitted predetermined plan. For example, when considering the introduction of an energy device 300 that is not included in the presented price plan, the customer inputs the type of the energy device 300 via the terminal 500. The arithmetic device 103 selects again the rate plan including the input energy device 300. Thereafter, the arithmetic device 103 can execute a fourteenth process to a fourteenth process, and determine a predetermined plan including the energy device 300 that the consumer considers introduction.

  Furthermore, the arithmetic unit 103 can also perform a simulation for comparing the determined predetermined plan with the current plan (the plan currently selected by the customer). The current plan is stored in the customer database 111 in advance, for example.

  For example, when a predetermined plan is transmitted, the consumer instructs a simulation on a simulation screen displayed by the application 510. The arithmetic unit 103 reads the current plan from the customer database 111 and compares it with a predetermined plan. The arithmetic device 103 transmits the comparison result to the terminal 500. The comparison result can be provided in various ways. The consumer can correct the information included in the current plan while referring to the comparison result.

In addition, a customer who has confirmed a predetermined plan or simulation result may desire to change the currently billed rate plan. For example, when a change from a current rate plan to a different rate plan (for example, a rate plan presented in a predetermined plan) is input in terminal 500, arithmetic unit 103 receives information on the change in the rate plan as energy business. A process of transmitting to the person system 600 is executed. The information regarding the change of the charge plan is, for example, personal information such as a customer's name, e-mail address, telephone number, and address, a charge plan currently contracted, and a charge plan presented in a predetermined plan. According to such an energy diagnosis system 100, the customer can easily change the rate plan (there is no need to contact the energy provider again). Such rate plan change processing can also be applied to the energy diagnosis system 100 according to the first embodiment.
<Modification>

  As described above, the plan database 115 stores a plurality of rate plans for each type of energy. On the other hand, there is a possibility that a new energy company will appear due to the liberalization of power supply, etc., and there is a charge plan specific to a certain region. As a consumer, there is a desire to consider these new rate plans when deciding on energy rate plans.

  Therefore, when information about a new rate plan is input from the terminal 500, the arithmetic device 103 in the present modification executes a process of storing the new rate plan in the storage device 101 (plan database 115).

  Information about the new rate plan can be entered in various ways. For example, the consumer can input a new price plan on the information registration screen displayed by the application 510. Alternatively, the consumer may provide the energy diagnosis system 100 with information on a new rate plan using SNS at the terminal 500.

  The arithmetic unit 103 determines whether or not the input new rate plan has already been registered, and if not, stores it in the plan database 115 as a new rate plan.

  In addition, when a new rate plan is registered, the arithmetic unit 103 may transmit an electronic coupon or the like of an energy rate discount to a consumer who has provided the information.

  The energy diagnosis system 100 can also execute various processes related to energy saving.

For example, the arithmetic device 103 compares the measured value obtained by the measuring device 4 with the currently contracted price plan, and transmits a warning message to the terminal 500 when the measured value is equal to or greater than a threshold value. For example, in a billing plan for electricity under contract, if the charge per unit increases when a certain amount of electricity is used, the arithmetic unit 103 stores the measured value transmitted from the measuring device 4. For example, when the remaining amount reaches 20% (an example of a threshold value) up to a certain amount, a warning message is transmitted to the terminal 500.

  Although several embodiments of the present invention have been described, these embodiments are presented by way of example and are not intended to limit the scope of the invention. These embodiments can be implemented in appropriate combination, and various omissions, replacements, and changes can be made without departing from the scope of the invention. Those embodiments and modifications thereof are included in the invention described in the claims and equivalents thereof as well as included in the scope and gist of the invention.

DESCRIPTION OF SYMBOLS 100 Energy diagnostic system 101 Storage apparatus 102 Memory 103 Arithmetic apparatus 104 Input apparatus 105 Output apparatus 106 Communication apparatus 110 Program 110A 1st process part 110B 2nd process part 110C 3rd process part 110D 4th process part 110E 5th 110F 6th processing unit 110G 7th processing unit 110H 8th processing unit 110I 9th processing unit 111 Customer database 112 Life log database 113 Calculation database 114 Equipment database 115 Plan database 200 Housing 300 Energy equipment 400 Measurement Equipment 500 Terminal 600 Energy company system

Claims (3)

A storage device;
The energy device that can be incorporated into a predetermined plan based on the device information stored in the storage device, including the type of energy device provided in the residence, and the type of energy that can be used in the residence, and the Tenth process for selecting a price plan for each type of energy,
An eleventh process for creating a plurality of patterns combining the selected energy device and the price plan;
Energy of the energy device selected for each of the plurality of patterns based on an estimated energy consumption amount per unit time for each energy device obtained in advance and a coefficient set in advance for each energy device. A twelfth process of calculating an estimated consumption amount;
A thirteenth process for applying the estimated energy consumption for each type of energy calculated in the twelfth process to the selected price plan and calculating charge data for each of the plurality of patterns;
A fourteenth process for determining the predetermined plan from the plurality of patterns based on the calculated fee data;
A fifteenth process of transmitting the determined predetermined plan to a consumer terminal;
An arithmetic unit for executing
An energy diagnostic system comprising: The arithmetic device executes a process of calculating an initial investment amount of an energy device used for the plurality of patterns for each of the plurality of patterns,
2. The energy diagnosis system according to claim 1, wherein, in the fifteenth process, the arithmetic device transmits the initial investment amount corresponding to the determined predetermined plan to the terminal. On the computer,
The energy device and the energy that can be incorporated into a predetermined plan based on the device information stored in the storage device, including the type of energy device provided in the residence, and the type of energy available in the residence. Execute the 10th process to select the rate plan for each type,
Executing an eleventh process of creating a plurality of patterns combining the selected energy device and the price plan;
Energy of the energy device selected for each of the plurality of patterns based on an estimated energy consumption amount per unit time for each energy device obtained in advance and a coefficient set in advance for each energy device. Execute a twelfth process of calculating an estimated consumption amount,
Applying the estimated energy consumption for each type of energy calculated in the twelfth process to the selected price plan, and executing a thirteenth process for calculating charge data for each of the plurality of patterns;
Based on the calculated fee data, a fourteenth process for determining the predetermined plan from the plurality of patterns is executed,
An energy diagnosis program for executing a fifteenth process of transmitting the determined predetermined plan to a customer terminal.

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