JP2019054584A - Power generation system evaluation method and power generation system evaluation device - Google Patents

Abstract

To provide a power generation system evaluation method capable of proposing an optimal combination of a storage battery capacity and a solar power generation device capacity for an expected power consumption amount of a building.SOLUTION: A power generation system evaluation method for evaluating the optimality of a combination of a solar panel capacity and a storage battery capacity, comprises a capacity condition input step (S101) of inputting a solar panel capacity and a storage battery capacity to be evaluated, an electric power condition input step (S104) of creating and inputting the power consumption amount of a house to be evaluated, the charged amount and the charging/discharging amount of a storage battery 2 in the house, and an expected amount (model data) of an electricity selling amount of the house, obtaining (S105) the electricity self-sufficient rate of the model data, the electricity selling rate of the model data, and an operating rate which is the rate of the model data of a discharging amount in the storage battery capacity, on the basis of the inputted conditions, and an evaluation value calculation step (S106) of further obtaining an evaluation value of the optimality on the basis of the electricity self-sufficient rate, the electricity selling rate, and the operating rate.SELECTED DRAWING: Figure 4

Description

  The present disclosure relates to a power generation system evaluation method and a power generation system evaluation apparatus.

Conventionally, when installing a power generation system including a storage battery at the time of home renovation, a prediction system for selecting facilities and materials that affect utility costs (for example, see Patent Document 1), a design support method (for example, a patent) Document 2) has been proposed.
The prior art described in Patent Document 1 includes consumption prediction means for calculating a utility cost after renovation when a selected facility or material is applied.
Moreover, the prior art described in Patent Document 2 determines whether or not a systematic combination process of combining a module group of photovoltaic power generation over a roof surface arranged in a plurality of directions and a combination of module groups can be electrically established. And an electric configuration calculation step for calculating the component and calculating the price.

Japanese Patent No. 5005838 JP 2006-278670 A

Although the above-mentioned conventional technology can calculate the cost required to install the selected equipment, the utility cost, etc., the storage battery capacity and the solar power generation device capacity are compared with the assumed power consumption in a building such as a house. It was not possible to propose the optimal combination.
That is, in a building, it is desirable to cover the power consumption by the generated power. Therefore, it is desirable that the power self-sufficiency rate is high. Such a power self-sufficiency ratio can be achieved by increasing the storage battery capacity and the photovoltaic power generation apparatus capacity.
However, since power consumption varies depending on the resident configuration and various specifications of the building, simply increasing the storage battery capacity or solar power generation device capacity may result in excessive specifications for the power consumption of the building. . When such an over-spec storage battery or solar power generation device is installed, the equipment cost increases, and power is wasted and stored, which is inefficient.

  Then, this invention aims at providing the electric power generation system evaluation method and electric power generation system evaluation apparatus which can propose the optimal combination of a storage battery capacity and a solar power generation device capacity | capacitance with respect to the power consumption assumed of a building. Yes.

In order to achieve the object, a power generation system evaluation method of the present disclosure includes:
A power generation system evaluation method for evaluating the optimum degree of combination of the capacity of a photovoltaic power generation device and a storage battery capacity with respect to the power consumption of a building,
Capacity condition input step for inputting capacity conditions of the photovoltaic power generation apparatus capacity and the storage battery capacity in the building to be evaluated;
A power condition input step for inputting the power consumption amount, the power sale power amount, the generated power amount, the charge amount and the discharge amount assumed in the building to be evaluated,
Based on each of the input conditions, a power self-sufficiency ratio that is a ratio of the amount of power other than the assumed power purchase amount in the assumed power consumption amount, and the assumed power sale in the assumed power generation amount. Obtaining a power selling rate that is a ratio of power capacity and an operating rate that is a ratio of the assumed discharge amount occupying the storage battery capacity, and further, the power self-sufficiency rate, the power selling rate, and the operating rate. An evaluation value calculation step for obtaining an evaluation value to be evaluated based on the optimality,
A power generation system evaluation method comprising:

In order to achieve the above object, a power generation system evaluation apparatus according to the present disclosure includes:
A power generation system evaluation device that includes an input unit, a calculation unit, and a display unit, and evaluates and displays the optimum degree of combination of the photovoltaic power generation device capacity and the storage battery capacity with respect to the power consumption of the building,
The computing unit is
The capacity conditions of the solar power generation device capacity and the storage battery capacity in the evaluation target building input from the input unit, the power consumption amount, the power sale power amount, the power generation power amount, the charge amount assumed in the evaluation target building, and Based on the discharge amount, the power self-sufficiency rate, which is the ratio of the amount of power other than the assumed purchased power amount in the assumed power consumption amount, and the ratio of the assumed power sale amount in the assumed generated power amount And an operation rate that is a ratio of the assumed discharge amount in the storage battery capacity, and further, based on the power self-sufficiency rate, the power sale rate, and the operation rate. Obtain an evaluation value to evaluate the optimum degree,
Based on the obtained evaluation value, a power generation system evaluation apparatus that displays the optimum degree of combination of the solar power generation apparatus capacity and the storage battery capacity is provided.

  In the power generation system evaluation method and the power generation system evaluation apparatus of the present disclosure, as a combination of the photovoltaic power generation capacity and the storage battery capacity, a combination that can efficiently consume power without wastefully selling or storing electricity is used. It is possible to provide a power generation system that can be proposed.

It is a whole system figure showing typically the whole power control system composition which carries out the power generation system evaluation method of Embodiment 1 of the present invention. It is a block diagram which shows the structure by the side of the house in the said power control system. It is a block diagram which shows the structure by the side of the management server in the said power control system. It is a flowchart which shows the flow of the process which calculates | requires the evaluation value which shows the optimal balance of the photovoltaic power generation capacity and storage battery capacity by the said power control system. It is explanatory drawing of the median value of the power consumption which specifies the house which extracts the electric power data which becomes the origin of model data in the said electric power control system. It is an electric power self-sufficiency rate characteristic figure which shows the relationship between the storage battery capacity and solar panel capacity | capacitance in Embodiment 1, and an electric power self-sufficiency rate. It is a power sale rate characteristic figure which shows the relationship between the storage battery capacity and solar panel capacity | capacitance in Embodiment 1, and a power sale rate. It is an operation rate characteristic figure which shows the relationship between the storage battery capacity in Embodiment 1, a solar panel capacity | capacitance, and the operation rate of a storage battery. It is an evaluation value characteristic view which shows the relationship between the storage battery capacity and solar panel capacity | capacitance in Embodiment 1, and an evaluation value. It is an evaluation value characteristic figure which shows the trial calculation example of the evaluation value with respect to the combination of a solar panel capacity | capacitance and a storage battery capacity. 3 is a time chart showing an example of changes in the amount of photovoltaic power generation and the amount of power consumption when a trial calculation is performed in a state where a storage battery is not installed in the first embodiment.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
(Embodiment 1)
First, an overall configuration of a power control system as a power generation system evaluation apparatus that implements the power generation system evaluation method of the first embodiment will be described with reference to FIG.

In this power control system, the houses H1, H2, H3,..., HX as buildings to be controlled are commercial power sources E as a system power network such as a power plant of a power company or a cogeneration facility installed in each region. (See FIG. 2). In the following description, when a specific one of the houses H1,..., HX is not pointed out, it is simply expressed as a house H.
These multiple houses are located throughout the country. In addition, each house is divided into a plurality of area sections set in advance based on energy saving standards according to the location, and heat insulation performance according to the area sections is given. For example, according to the regional division based on the energy saving standard of 2013, the whole country is divided into 1-8 regional divisions.

  Each house H includes at least a solar panel 1 as a solar power generation device and a storage battery 2 that temporarily stores electric power. Furthermore, these houses H are each connected to the management server 5 via an external communication network N such as the Internet, and send / receive data such as measurement values and calculation processing results to / from the management server 5 and various control signals. Are sent and received. In the first embodiment, by using actual measurement data such as power consumption sent from these houses H to the management server 5, the power self-sufficiency rate, the power selling rate, and the storage battery operation of the house (house) to be estimated Calculate the rate.

  Although not shown, the management server 5 is constituted by an information processing apparatus including a CPU, a memory such as a RAM and a ROM, and a communication interface 51 (FIG. 3) that performs communication via the communication network N controlled by the CPU. For example).

(Composition on the housing side)
Next, a configuration on the house H side will be described based on FIG. 2 which is a block diagram schematically showing a power system and a communication system of a house to which the power control system of the first embodiment is applied.
As a power supply system for each house H, a distribution board 10 is provided.
The distribution board 10 is connected to the commercial power source E, and is connected to the solar panel (solar power generation device) 1, the storage battery 2, and the power load group 3 of the house H.

  The solar panel 1 is a device that generates sunlight by converting sunlight into electric power by using a solar cell. This solar panel 1 can supply electric power only during a time period in which sunlight can be received. Moreover, the DC power generated by the solar panel 1 is usually used after being converted to AC power by a power conditioner (not shown). The solar panels 1 installed in these houses H have a plurality of specifications, and the power generation capacity and the like differ depending on the specifications. The difference in specifications for each house H will be described later on the management server 5 side. Stored in the residence information database 53a.

  On the other hand, the storage battery 2 is also subjected to DC-AC conversion by a power conditioner (not shown) in the same manner as the solar panel 1, and the storage (charging) and discharging are controlled. This storage and discharge control is performed, for example, by storing, in the storage battery 2, low-power electric power such as midnight power supplied from the commercial power source E or power generated by the solar panel 1. Control is performed so that discharging is performed during periods of high power prices. In addition, in consideration of the power sale price, etc., control is also included in which part or all of the generated power is discharged to the commercial power source E side for power sale. Note that specifications such as the capacity of the stored battery 2 and the rated output are also stored in association with the house H in a later-described residence information database 53a on the management server 5 side.

  Moreover, you may include the electric vehicle MV as a storage battery. A storage battery (not shown) mounted on the electric vehicle MV can be connected to the distribution board 10 via the EV power conditioner 8. A storage battery (not shown) mounted on the electric vehicle MV can be used as the storage battery 2 to be discharged for the electric power load group 3 of the house H, while being a load when charging for running. The electric vehicle MV includes not only a motor only as a drive source but also a plug-in hybrid vehicle equipped with an engine.

  The power load group 3 is composed of a plurality of power loads that are driven by consuming electric power. Examples of the power load include lighting devices (not shown) such as a hot water supply device 31, an air conditioner 32, a lighting stand, and a ceiling light. And household appliances (not shown) such as refrigerators and televisions, cooking devices, and the like. The distribution board 10 and each power load of the power load group 3 are connected via a plurality of branch circuits 20a and 20b to 20n.

The power consumption of the power load group 3 and the like is measured by the measuring device 4.
That is, the measuring device 4 includes the amount of electric power purchased from the commercial power source E toward the distribution board 10, the amount of electric power sold from the house H toward the commercial power source E, and the power generated by the solar panel 1. The amount of electric power, the amount of discharged electric power discharged from the storage battery 2, and the amount of charged electric power charged in the storage battery 2 are measured. Furthermore, you may make it measure the electric power consumption supplied to the electric power load group 3 via each branch circuit 20a-20n. The power consumption can be obtained from the amount of purchased power + (the amount of generated power−the amount of sold power) without performing the measurement.

  Moreover, the measurement of each electric energy by the measuring device 4 can be performed by integrating every arbitrary time such as 1 second unit, 1 minute unit, and 1 hour unit. And the data of the measured value measured by the measuring device 4 are input and stored in a power consumption history database 53b described later on the management server 5 side.

  Each house H is provided with a communication interface 19. The communication interface 19 is connected to the management server 5 via an external communication network N such as the Internet, and the measurement value of the measurement device 4 and the calculation processing result in the management server 5 are communicated with the management server 5. Send and receive data and send and receive control signals.

  Further, the house control unit 18 can control the supply of power from the distribution board 10 to the power load group 3 including the storage battery 2, and this house control unit 18 is an operation plan sent from the management server 5. Based on the above, the operation of the power load group 3 including the storage battery 2 is performed.

(Management server configuration)
Next, the configuration of the management server 5 will be described with reference to FIG.
The management server 5 includes a communication interface 51, a control unit 52 that performs various controls, a house information database (DB) 53a, a power consumption history database (DB) 53b, a power price database (DB) 53c, and a weather database ( DB) 53d and an operation pattern database (DB) 53e.

  The communication interface 51 sends measurement values, processing requests, and the like transmitted from each house H via the communication network N to the control unit 52 of the management server 5. Further, the communication interface 51 has a function of sending data stored in the various databases 53 a to 53 e, results of arithmetic processing performed by the control unit 52, an update program, and the like to each house H. The calculation processing result performed by the control unit 52 includes so-called HEMS (Home Energy Management System) control that saves energy by increasing the efficiency of power use at home.

  The house information database 53a includes a house code (identification number) given to each house H, an address associated with the house code, a building year, heat insulation performance, floor plan and floor area, electric wiring, members used, sunlight Information on specifications of various facilities such as specifications of the panel 1 (power generation capacity) and specifications of the storage battery 2 (storage capacity, rated output) is stored. Further, in the house information database 53a, the actual power generation amount per unit time is stored for each house H in association with weather data (amount of solar radiation). For example, since the installation conditions of the solar panels 1 are different for each house H, even if the solar radiation amount is the same in the same region, the power generation amount varies, so that data is stored for each house H.

In the power consumption history database 53b, power data including power consumption measured or calculated in each house H is received and stored via the communication interface 51. The power consumption history is stored for each unit time and is associated with a calendar such as a day of the week. In the power consumption history database 53b, the power consumption of the air conditioning load such as the air conditioner 32 and the hot water supply load such as the hot water supply device 31 and the weather conditions such as the temperature are not easily affected by the weather conditions such as the temperature. The power consumption of other loads may be stored in categories classified by load.
Furthermore, in the power consumption history database 53b, for each house H, the actual amount of generated power per unit time is stored in association with weather data (amount of solar radiation). For example, since the installation conditions of the solar panels 1 are different for each house H, even if the solar radiation amount is the same in the same region, the power generation amount varies, so that data is stored for each house H. In addition, the amount of power purchased per unit time is also stored in the power consumption history database.

  In the electric power price database 53c, the electric power price for each time zone (the electric power purchase price as seen from the resident side) and the price at which the electric power company purchases the electric power generated by the solar panel 1 (the electric power sale price as seen from the resident side) ) Is stored.

The weather database 53d stores weather forecast data for the next day, such as the temperature and solar radiation in various parts of the country where each house H is located, which is received via a communication network N from a server (not shown) such as the Japan Meteorological Agency or a weather forecast company. Yes. Furthermore, the meteorological database 53d may store actual meteorological data every moment, weather data such as temperature, humidity, and amount of sunshine, and may be used as past data.
In the operation pattern database 53e, various operation patterns of the power load group 3 and the storage battery 2 installed in each house H are stored in association with weather data.

The control unit 52 includes an operation planning unit 52a and an operation monitoring unit 52b.
The operation planning unit 52a predicts the necessary power consumption, power generation amount, and operation pattern for each hour of the next day based on the weather forecast and past power consumption data of the next day, and the storage operation time and discharge operation of the storage battery 2. The time, hot water storage operation time by the hot water supply device 31 and the like are set.

  Based on the data sent from the house H, the operation monitoring unit 52b monitors the operation state using the power in the house H, and when an abnormality including the abnormality of the storage battery 2 occurs, it reports an abnormality. Perform the appropriate process. In addition, as a process which reports this abnormality, the process displayed by the display apparatus 18a, the process which reports to the management company of the house H with a telephone, an email, etc. via the communication network N etc. are performed.

(Power generation system evaluation method)
The power generation system evaluation method according to the first embodiment is executed by the management server 5 and a personal computer (hereinafter referred to as a personal computer) PC that can be connected to the management server 5 via the communication network N.

As is well known, this personal computer PC includes an input unit (not shown) for performing input from a communication network or by keyboard operation, an arithmetic unit (not shown) for performing various arithmetic processes, and a display screen SC as a display unit. .
And in this personal computer PC, based on the setting condition data regarding the house to be evaluated (hereinafter, the house to be estimated is distinguished from the existing house H and called the house) and the data of the house H stored in the management server 5. Then, a power self-sufficiency rate, a power selling rate, and a storage battery operating rate are calculated, and further, based on these, a calculation for obtaining an evaluation value indicating an optimal balance between the solar panel capacity and the storage battery capacity is performed.

The evaluation value of the optimum balance is a value indicating the degree of power self-sufficiency, no wasteful power generation, and the ability to use the storage battery 2 without waste.
And this evaluation value is the solar panel capacity and the storage battery capacity when, for example, a new house is built or when a solar panel 1 is newly installed or expanded, or when a storage battery 2 is newly installed or expanded in an existing house. Can be used to set the optimal combination.

  Here, in this Embodiment 1, the case where trial calculation object is what is called an all-electric housing is mentioned as an example. An all-electric house is a house where cooking, air conditioning, lighting, hot water supply, etc. are all covered by electricity.

(Trial calculation)
Hereinafter, the flow of the evaluation value calculation executed in the personal computer PC will be described with reference to the flowchart of FIG.

This power self-sufficiency is started by starting trial calculation software on a personal computer PC.
In the first step S101, the residence conditions are read. This residence condition is manually input in advance using a residence condition input screen (not shown) displayed on the display screen SC of the personal computer PC, and the entered residence condition is read.

Here, the residence conditions are selected based on the housing H that is likely to have the same amount of power consumption as the residence to be estimated, and then the storage battery capacity to be calculated, the amount of power consumed according to the solar panel capacity, the amount of generated power, the sales This is a setting condition for creating model data (each value assumed in the residence) of the electric power amount, the charge amount, and the discharge amount.
Specifically, the residence conditions include the area where the residence is built, the resident composition (number of households or family composition, etc.), the type of house (steel frame, wood, etc.), and the total floor area. Furthermore, the residence conditions include a storage battery capacity (which may be a storage battery model or the like) that is considered for installation by renovation, the presence or absence of an electric vehicle MV, and a capacity condition of a solar panel capacity including existing or added.

  That is, the house H, which has a common area with the trial residence, tends to have similar heat insulation performance, air conditioning such as cooling and heating, and other power consumption. Similarly, in a house H having a common or similar resident configuration, power consumption amounts such as air conditioning, hot water supply, and lighting tend to be similar.

  Therefore, by inputting the area classification and resident composition as the residence conditions as described above, the residence whose power consumption is similar to that of the trial residence from among the residences H in which data is input to the management server 5 H can be searched. In addition, by inputting the storage battery capacity and solar panel capacity for trial calculation of the evaluation value as the residence condition, the actual power generation amount, power sales amount, power purchase amount, charge amount and discharge amount in the same combination of houses are used. Thus, an assumed value of these values can be created.

  Therefore, in the next step S102, a house that matches the house condition read in step S101 is searched from the houses H for which data has been input to the management server 5, and the search result is displayed on the display screen SC. Do.

That is, a list of a plurality of houses H that match the residence conditions is displayed on the display screen SC.
In addition, in this Embodiment 1, since the case of the renovation in the house in which the storage battery 2 is not installed is illustrated, the house H in which the storage battery 2 is not installed as the house H in which the conditions match the house to be calculated You may make it search. In this case, as the model data of the charge / discharge amount described later, data calculated from the model data of the power generation amount and the power consumption amount may be used.

  Step S103 of the dotted frame following step S102 is performed by manual input operation by the operator after display of the searched house H, and the house H to be used for trial calculation is selected from the displayed houses H. .

  In this case, the house H to be selected selects one house H having actual measurement data that satisfies the total power consumption and other conditions from the plurality of searched houses H. This selection may be performed automatically, but in the first embodiment, it is performed manually as described above.

That is, as the house H used for the trial calculation, basically, the one having a median total power consumption and private power consumption is selected from the plurality of houses H (see FIG. 5 Da1). Therefore, although the median value may be automatically selected, the reason for selecting manually as in the first embodiment is as follows.
The data of the house H is normally measured over the entire period of the predetermined period (for example, one year), in addition to the power consumption (the amount of generated power, the amount of purchased power, the amount of charge / discharge, etc.). It may not always be. Therefore, the operator confirms whether or not the data is normally measured for a predetermined period by visual inspection, and if there is a problem in the data Da1 with the total power consumption and the personal power consumption being the median, In the vicinity thereof (for example, data Da2 in FIG. 5), it is confirmed whether or not the measurement is normally performed over a predetermined period (for example, one year) in the same manner as described above. Select.

For the selected house H, as described above, power data including power consumption, generated power, purchased power, and charge / discharge is input to the management server 5. Further, the power data including the power consumption amount, the generated power amount, the purchased power amount, and the charge / discharge amount is data for every predetermined time over one year. In the first embodiment, one hour or 30 minutes. This is data obtained by accumulating each data for a predetermined period (for example, one year). The purchased power amount can be obtained as a value obtained by subtracting the generated power amount from the consumed power amount, while the sold power amount can be obtained as a value obtained by subtracting the consumed power amount from the generated power amount. Therefore, it is not always necessary to download all of the power consumption, generated power, and purchased power.
Similarly, in addition to reading the power consumption amount from the house H as it is, the power consumption amount can be calculated from the generated power amount, the purchased power amount, and the sold power amount. That is, it is also possible to obtain the amount of electric power purchased + (the amount of generated electric power−the amount of electric power sold) = the total electric energy consumed.

  In step S104 subsequent to step S103, an evaluation value is obtained from actual measurement data such as the amount of power consumption, the amount of generated power, the amount of purchased power, the amount of charge and the amount of discharge of the house H selected in step S103, and data of various specifications. Power consumption [kWh], generated power [kWh], purchased power [kWh], discharge [kWh] (or charge from solar panel 1 = PV charge [kWh]) Create and enter model data. These model data may be input in advance based on the area of the house, the type of house, the floor area, the resident composition, and the like.

  Here, first, actual measurement data of the power consumption amount, the generated power amount, the purchased power amount, and the discharge amount of the selected house H will be described. In the first embodiment, the solar panel 1 and the storage battery 2 over time. In consideration of the special deterioration, the house H to be searched in step S103 is searched only for the house H that has a short age (for example, within two years and over one year) and hardly deteriorates. Yes. Therefore, each actual measurement data of the selected house H is also data that has a short age (for example, within two years) and hardly deteriorates in the solar panel 1 or the storage battery 2. It should be noted that the house H to be searched is not limited to a house with a short age, and the actual measurement data such as the total amount of generated power is corrected to be equivalent to the data at the time of new construction according to the age of the house H. May be.

Next, model data will be described.
In the case of the first embodiment, the evaluation value indicates how much the storage battery 2 and the solar panel 1 are installed when the storage battery 2 is newly installed by renovation or when the solar panel 1 is added or newly installed. It is used to determine whether it is better to set a combination of capacities.

  Therefore, as model data, model data of power consumption, generated power, purchased power, discharge (or pv charge) according to the storage battery capacity and solar panel capacity input as the residence conditions in step S101. Form.

  Here, the storage battery capacity and solar panel capacity of the selected house H are known in advance. Further, the storage battery input in step S101 with respect to the relationship between the storage battery capacity and the solar panel capacity in the selected house H, and the power consumption, generated power, purchased power, and discharge (pv charge). An arithmetic expression to be converted into model data of the generated power amount, the purchased power amount, and the discharged amount (pv charge amount) when replaced with the capacity and the solar panel capacity is input to the personal computer PC in advance. In addition, regarding power consumption, if there is a difference in specifications between the estimated residence and the selected house H, or a difference in the resident composition (number of people or number of households), the power consumption of the selected house H is calculated. An arithmetic expression to be converted into the power consumption amount of the house to be estimated is input to the personal computer PC in advance.

  Accordingly, in step S104, the storage battery capacity, the solar panel capacity, and the power consumption according to the resident configuration input in step S101 from the power consumption, generated power, purchased power, and discharge of the selected house H, The amount of generated power, the amount of purchased power, and the amount of discharge are calculated as model data.

In subsequent step S105, the model data calculated in step S104 is used to calculate a power self-sufficiency rate, a power selling rate, and a storage battery operating rate, which are used for calculation of an evaluation value representing evaluation of the optimum balance.
First, the power self-sufficiency rate is the ratio of the amount of power that has not been purchased out of the total power consumption for one year, and can be obtained by the following equation (1).
Electric power self-sufficiency rate (%) = [1- (Electricity purchased [kWh] / Energy consumed [kWh])] × 100 (1)
That is, the self-sufficiency rate becomes 100% when the amount of purchased electric power becomes 0 throughout the year.

Further, the power self-sufficiency rate can also be obtained from the following equation (2).
Power self-sufficiency rate (%) = [(self-power consumption [kWh] + discharge amount (= PV charge amount) [kWh]) / power consumption [kWh]] × 100 (2)

Here, an example of the relationship between the power self-sufficiency rate, the solar panel capacity, and the storage battery capacity is shown in FIG.
As shown in this figure, it can be seen that the larger the solar panel capacity and the storage battery capacity, the higher the power self-sufficiency rate.

Next, the power sale rate represents the ratio of the surplus power amount that is not used in the house to the total power generation amount, and is obtained by the following equation (3).
Electricity sales rate (%) = (Amount of electricity sold [kWh] / Amount of electricity generated [kWh]) × 100 (3)
FIG. 7 shows the relationship between the power sale rate, the solar panel capacity, and the storage battery capacity. As shown in FIG. 7, the power sale rate increases as the solar panel capacity increases, but the use in the house tends to decrease as the storage battery capacity increases.

By the way, in recent years, an output suppression problem has arisen. That is, in such a situation, the output is suppressed so that power cannot be sold so that the energy (electric power) production amount in the entire system power such as the commercial power source E does not exceed the consumption amount. . In addition, the unit price of electricity sales is expected to decrease in the future. From such environmental considerations and economical viewpoints, it is preferable to keep the power selling rate as low as possible.
That is, a low solar power selling rate indicates that the generated power can be effectively used in the house. The high power selling rate indicates that the solar panel capacity is larger than the required capacity in the house. Considering from an environmental point of view, the solar panel 1 requires energy at the time of manufacture and disposal, and therefore it is desirable that the solar panel 1 be within the required capacity in the house.

Next, the storage battery operating rate is relative to the storage battery capacity. It is the ratio of the electric power used in the house H, and it calculates | requires by following formula (4).
Battery operating rate (%)
= (Discharge amount (= PV charge amount) [kWh] / storage battery capacity [kWh]) × 100 (4)

  FIG. 8 shows the relationship between the storage battery operation rate, the storage battery capacity, and the solar panel capacity. As shown in this figure, the larger the storage battery capacity, the lower the storage battery operating rate. Moreover, a storage battery operation rate falls, so that solar panel capacity | capacitance is large.

Here, the level of the storage battery operation rate will be described. A high storage battery operation rate indicates that the play time of the storage battery 2 is short. Considering from an environmental point of view, the storage battery 2 also requires energy at the time of manufacture and disposal in the same manner as the solar panel 1, so that it is desirable that the storage battery 2 be contained within the required capacity in the house.
That is, it is desirable that the battery operating rate is close to 100% with little play time.

In step S106 which proceeds after obtaining the power self-sufficiency rate, the power selling rate, and the storage battery operating rate in step S105, an evaluation value is calculated.
This evaluation value is a value indicating the optimum balance of the power self-sufficiency, the capacity of the solar panel 1, and the capacity of the storage battery 2.
Specifically, the evaluation value is obtained by the following equation (5).
Evaluation value [%] = Electricity self-sufficiency rate [%] x Solar power consumption rate [%]) x Battery operating rate [%] (5)
In addition, it is solar self-consumption rate = 1-electric power selling rate.
Therefore, the evaluation value is high for a combination that has a high power self-sufficiency rate, a high solar self-consumption rate (low power selling rate), and a high storage battery operating rate.

  As described above, the capacity of the solar panel 1 and the capacity of the storage battery 2 do not have to be increased suddenly, and the solar panel 1 does not perform unnecessary power generation while achieving self-sufficiency at a high rate. It is desirable to utilize the storage battery 2 without waste. Thus, the above-described evaluation value shows an optimum balance between a high self-sufficiency rate, efficient power generation, and an operation rate with less dead time of the storage battery 2.

  In step S107, which proceeds after the calculation of the evaluation value, an evaluation value characteristic based on the calculated evaluation value is displayed on the display screen SC. As shown in FIG. 9, this evaluation value characteristic indicates an evaluation value according to the storage battery capacity and the solar panel capacity. Although a plurality of storage battery capacities are described in FIG. 9, only the evaluation value characteristics displayed in step S107 are those according to the storage battery capacity set in step S101.

  For example, looking at the characteristics of the storage battery capacity = 1 kWh in FIG. 9, the evaluation value = about 12% is the highest when the solar panel capacity is 2 kW. In this case, referring to the characteristics of the power self-sufficiency rate in FIG. 6, the combination C1 with the storage battery capacity = 1 kWh and the solar panel capacity = 2 kW has a power self-sufficiency rate of about 20%. Further, referring to the characteristics of the power sale rate in FIG. 7, in the case of the combination C1, the power sale rate is about 25%. Further, referring to the characteristics of the operating rate in FIG. 8, in the case of the combination C1, the operating rate is about 80%.

  On the other hand, looking at the characteristics of the storage battery capacity = 5 kWh in FIG. 9, the evaluation value = 22.5% is the highest when the solar panel capacity is 4 kW. In this case, referring to the characteristics of the power self-sufficiency rate in FIG. 6, the combination C2 with the storage battery capacity = 5 kWh and the solar panel capacity = 7 kW has a power self-sufficiency rate of about 39%. Further, referring to the characteristics of the power sale rate in FIG. 7, in the case of the combination C2, the power sale rate is about 26%. Further, referring to the characteristics of the operation rate in FIG. 8, in the case of the combination C2, the operation rate is about 80%.

  Further, looking at the characteristics of the storage battery capacity = 11 kWh in FIG. 9, the evaluation value = 33% is the highest when the solar panel capacity is 7 kW. In this case, referring to the characteristics of the power self-sufficiency rate in FIG. 6, the combination C3 of the storage battery capacity = 11 kWh and the solar panel capacity = 7 kW has a power self-sufficiency rate of about 62%. Further, referring to the characteristics of the power sale rate in FIG. 7, in the case of the combination C3, the power sale rate is about 31%. Further, referring to the characteristics of the operating rate in FIG. 6, in the case of the combination C3, the operating rate is about 77%.

  Then, in step S107, which proceeds after the evaluation value is calculated, an evaluation value characteristic graph (see FIG. 9) showing the relationship between the storage battery capacity and the solar panel capacity and the evaluation value is displayed on the display screen SC. Therefore, it is possible to know the optimum storage battery capacity for the capacity of the currently installed solar panel 1. Instead of displaying the evaluation value characteristic graph, an optimal model of the storage battery 2 may be displayed.

  In addition, as shown in FIG. 9, it can be seen that the evaluation value characteristics differ depending on the combination of the storage battery capacity and the solar panel capacity, and that the power self-sufficiency rate, the power selling rate, and the storage battery operating rate are different respectively. . When the evaluation value is the highest value, the balance between the storage battery capacity and the solar panel capacity is the best.

(Operation of Embodiment 1)
Next, the operation of the first embodiment will be described.
In the explanation of this function, in the renovation of a residence where the storage battery 2 is not installed, when the storage battery 2 is newly installed, an example of a meeting in which the specifications of the storage battery 2 are determined between the resident and the sales staff is taken as an example. I will give you.

In addition, as a premise, the management server 5 stores the power consumption amount, the generated power amount of the solar panel 1, the charge power amount of the storage battery 2, and the discharge power amount data in a plurality of constructed houses H for a predetermined time ( For example, it is input in units of 1 hour and 30 minutes. The management server 5 stores data for each hour, and also stores data for each day, week, month, and year obtained by integrating the data.
Furthermore, in the management server 5, data regarding specifications for each house H is also stored in advance.

  At the time of the above meeting, the operator of the personal computer PC who is a sales representative first has the personal computer PC to determine the area classification, the resident composition, the type of residence, the capacity of the solar panel 1 according to the location of the renovation residence. The operation for calculating the evaluation value is started after inputting the residence conditions such as the storage battery capacity to be installed and the presence or absence of the electric vehicle MV.

  As a result, first, an all-electricity-type house H having a resident configuration with a common or similar resident composition and a common residence and region classification from among the houses H input to the management server 5 is calculated. Search and display the search result (S102). In the first embodiment, the search target is limited to the house H whose age is shallow.

  Next, the operator of the personal computer PC selects a house H in the vicinity of the median value of the total power consumption and private power consumption for one year or in the vicinity thereof from the searched houses H (S103). In response to this selection operation, the personal computer PC, based on the actual measurement data of the selected house H, assumes the estimated power consumption, generated power, and purchased power according to the solar panel capacity and storage battery capacity in the residence setting conditions. Then, model data of the charge / discharge amount is created (S104).

Further, the personal computer PC calculates the power self-sufficiency rate, the power selling rate, and the storage battery operating rate based on the created model data (S105), and thereafter calculates the evaluation value based on these values (S106), The characteristic diagram is displayed on the display screen SC (S107).
Therefore, the operator can know the evaluation of the capacity of the solar panel 1 installed in the residence and the storage battery capacity set as the residence conditions. Furthermore, by displaying the evaluation value characteristic graph shown in FIG. 9, when there is a combination having an evaluation value higher than the evaluation value according to the combination of the input solar panel capacity and the storage battery capacity, the combination is selected. Knowing it, it becomes possible to consider changing the storage battery capacity, adding solar panels 1 and the like as necessary.

The change of the storage battery capacity and the addition of the solar panel 1 will be described with reference to FIG.
FIG. 10 shows an evaluation value characteristic graph when the solar panel capacity is 3 kWh, 4 kWh, and 5 kWh. In FIG. 10, the horizontal axis represents the storage battery capacity.

In each evaluation value characteristic graph, when there is no storage battery 2, since the operation rate of the storage battery 2 is 0%, the evaluation value = 0.
Here, considering each evaluation value characteristic, first, the solar panel capacity 3 kWh has the maximum evaluation value (about 22%) when the storage battery capacity is around 6 kWh. Therefore, in the case of a solar panel capacity of 3 kWh, a combination with the best balance is obtained when the storage battery capacity is 6 kWh. For example, when the capacity of the existing solar panel 1 in the residence is 3 kW, the storage battery capacity is preferably 6 kW.

In this case, the power self-sufficiency rate is about 36%, the operation rate of the storage battery 2 is about 63%, and the power sale rate is about 9%.
As can be seen from the evaluation value characteristics, when the storage battery capacity is larger than this, the operating rate increases (see FIG. 8), and when the solar panel capacity is increased, the power selling rate increases (see FIG. 7). .

  Next, the case where the solar panel capacity is increased as a trial and the solar panel capacity is set to 4 kWh is examined. In this case, the evaluation value becomes maximum (about 27%) when the storage battery capacity is around 9 kWh. Therefore, in the case of a solar panel capacity of 4 kWh, a combination with the best balance is obtained when the storage battery capacity is 9 kWh.

In this case, the power self-sufficiency rate is about 46%, the operation rate of the storage battery 2 is about 65%, and the power sale rate is about 10%.
As can be seen from the evaluation value characteristics, when only the storage battery capacity is larger than this, the operating rate increases (see FIG. 8), and when the solar panel capacity is increased, the power selling rate increases (see FIG. 7). ).

  Next, in the case of a solar panel capacity of 5 kWh, the evaluation value becomes maximum (about 32%) when the storage battery capacity is around 10 kWh. Therefore, in the case of a solar panel capacity of 5 kWh, a combination with the best balance is obtained when the storage battery capacity is 10 kWh.

In this case, the power self-sufficiency rate is about 54%, the operation rate of the storage battery 2 is about 70%, and the power sale rate is about 17%.
As can be seen from the evaluation value characteristics, when the storage battery capacity is larger than this, the operating rate increases (see FIG. 8), and when the solar panel capacity is increased, the power selling rate increases (see FIG. 7). .

  As described above, by displaying the graph of the evaluation value characteristics for the combination of the solar panel capacity and the storage battery capacity on the display screen SC of the personal computer PC, the sales staff and the renovation requester who operate the personal computer PC The optimum specification can be determined with reference to FIG.

  In addition, when displaying the optimal combination of storage battery capacities as described above, a plurality of types of storage batteries 2 (products and prices) having storage battery capacities are also displayed at the same time. This makes it easier to determine the specifications.

A description of model data is added below.
First, in measuring the total power consumption, total generated power, and total purchased power for one year, the house control unit 18 measures and accumulates each value every predetermined time (for example, 1 hour or 30 minutes). . And in the management server 5, this is read and accumulate | stored for every predetermined time (for example, every day). For example, the power consumption amount is often different between weekdays and holidays other than weekdays. Therefore, also when creating model data, the model data corresponding to the pattern is calculated according to the weekday pattern in the measurement data and the pattern other than the weekday. Then, the model data for each day is accumulated for one week, and model data for the amount of power consumption, generated power amount, purchased power amount, and discharge amount for one week is created. Then, the model data of the monthly power consumption, generated power amount, and purchased power amount obtained by integrating this is created, and the model data of the total annual power consumption, total generated power amount, and total purchased power amount are further generated. create.
Therefore, highly accurate model data based on actual measurement data can be created in this way, and the power self-sufficiency rate, storage battery operating rate, power selling rate, and evaluation value calculated based on this can be determined with high accuracy.

FIG. 11 shows an example of calculation results of the power consumption, generated power, purchased power model data, and power self-sufficiency rate.
FIG. 11 shows the calculated photovoltaic power generation amount and power consumption amount. From April to October, there are many times when the solar power generation amount exceeds the power consumption amount, but the winter season from December to February. Shows that the amount of power consumption often exceeds the amount of photovoltaic power generation.
Since detailed model data is created in this way, the power self-sufficiency rate, the storage battery operating rate, the power selling rate, and the evaluation value calculated based on the model data are also highly accurate values.

(Effect of Embodiment 1)
The effects of the first embodiment of the present disclosure are listed below.
1) The power generation system evaluation method of Embodiment 1 is
A power generation system evaluation method for evaluating the optimum degree of combination of solar panel capacity and storage battery capacity with respect to power consumption of a building,
Capacity condition input step (S101) for inputting capacity conditions of solar panel capacity and storage battery capacity in the residence to be evaluated;
A power condition input step (S104) for creating and inputting model data that is an amount of power consumption, charge / discharge amount, electric power sales amount, and electric power generation amount assumed in the residence to be evaluated;
Based on each input condition, the power self-sufficiency ratio, which is the ratio of the energy other than the purchased power to the model data, and the sales, which is the ratio of the sold power to the model data. The power rate and the operating rate that is the ratio of the model data of the discharge amount to the storage battery capacity are obtained (S105), and the optimum degree is evaluated based on the power self-sufficiency rate, the power selling rate, and the operating rate. And an evaluation value calculation step (S106) for obtaining a value.
Therefore, the optimal combination of the solar panel capacity and the storage battery capacity can be known. In other words, the solar panel capacity and the storage battery capacity need not be increased as much as possible, and while achieving a high degree of self-sufficiency, the solar panel 1 does not perform unnecessary power generation and uses the storage battery 2 without waste. It is desirable to do. Based on the above evaluation values, it is possible to know the combination of the solar panel capacity and the storage battery capacity that can obtain an optimum balance between a high self-sufficiency ratio, efficient power generation, and a high operation rate of the storage battery 2.

2) The power generation system evaluation method of Embodiment 1 is as follows:
The evaluation value is obtained as a value that is proportional to the power self-sufficiency rate and the operation rate and inversely proportional to the power sale rate.
Therefore, the combination of the solar panel capacity and the storage battery capacity capable of obtaining the optimum balance between the high self-sufficiency ratio, the efficient power generation, and the high operation rate of the storage battery 2 can be known more reliably.

3) The power generation system evaluation method of Embodiment 1 is
The evaluation value is obtained by calculation of power self-sufficiency rate × operating rate × (1−power selling rate).
Therefore, the combination of the solar panel capacity and the storage battery capacity capable of obtaining the optimum balance between the high self-sufficiency ratio, the efficient power generation, and the high operation rate of the storage battery 2 can be known more reliably.

4) The power generation system evaluation method of Embodiment 1 is
The power self-sufficiency rate is obtained by dividing a value obtained by adding the assumed discharge amount to the self-consumption power amount by the assumed power consumption.
Therefore, the power self-sufficiency rate can be calculated with high accuracy.

5) The power generation system evaluation method of Embodiment 1 is
The power condition input step (S104)
Data of building specifications including the output capacity of the solar panel 1, the presence or absence of the storage battery 2, and the capacity of each of the plurality of existing houses H, the regional data of each house H, the resident composition data of each house H, A data input step of associating the power data measured during a predetermined period of each house H with each house H and inputting it into the database of the management server 5;
An extraction step for extracting from the data input to the database of the management server 5 data for trial calculation including the power data of a plurality of houses H according to the location of the house to be evaluated and the resident configuration;
Based on the extracted power data for trial calculation, the power consumption amount, power generation amount, power purchase amount, charge / discharge amount for a predetermined period according to the specifications of the house to be evaluated are obtained, and the power consumption amount for these predetermined periods, Obtaining model data of power consumption, generated power, purchased power, charge / discharge based on the generated power, purchased power, charge / discharge, and capacity conditions.
Therefore, the model data is created based on the actually measured power data of the house H of the same area and the resident configuration as the trial calculation target house, so that the evaluation value can be calculated with higher accuracy.

6) The power generation system evaluation method of Embodiment 1 is as follows:
In the data input step, as the power data, predetermined time data measured every predetermined time and predetermined period data stored as data for a predetermined period are input to the database.
In this way, since power data in fine units is accumulated and used as power data for a predetermined period (predetermined period data), highly accurate model data can be created. Further, based on this highly accurate model data, it is possible to calculate a highly accurate evaluation value.

7) The power generation system evaluation method of Embodiment 1 is
In the extraction step, each piece of power data of the house H selected based on the median value of the total power consumption is extracted from the house extracted according to the house to be calculated, the area classification where it is located, and the resident composition.
That is, power data such as the amount of power consumption varies greatly depending on the house H, and the same value is rarely obtained in the plurality of houses H. For this reason, for example, the data of the average value of the house H is likely to be affected by the power data of the maximum value and the minimum value of the house H, and the accuracy may be lowered, and the mode value is difficult to obtain. Therefore, by selecting the house H having the median power consumption, it becomes possible to extract the data of the house H that is consuming the most standard power consumption, thereby obtaining highly accurate model data. It becomes possible.
Furthermore, by not limiting to only the median value, it becomes possible to eliminate the fact that there is a flaw in other data in the housing H with the total power consumption being the median value. Can be increased.

8) The power generation system evaluation method of Embodiment 1 is as follows:
In the device condition input step, the storage battery capacity of the electric vehicle is included as the storage battery capacity.
Therefore, the trial calculation accuracy when the electric vehicle MV is held is further increased.

9) The power generation system evaluation apparatus of Embodiment 1 is
This is a power generation system evaluation apparatus that has an input unit, a calculation unit, and a personal computer PC equipped with a display screen SC, and evaluates and displays the optimum degree of combination of the solar panel capacity and the storage battery capacity with respect to the power consumption of the building. And
The computing part of PC PC
Capacity conditions of solar panel capacity and storage battery capacity at the evaluation target residence input from the input unit, and model data of the assumed power consumption, charge / discharge amount, electric power sales amount, generated power amount of the evaluation target residence , Based on, the power self-sufficiency ratio that is the ratio of the amount of power other than the purchased power amount to the amount of power consumption of the model data, Obtain the operation rate, which is the ratio of the model data of the discharge amount to the storage battery capacity, and further obtain the evaluation value that evaluates the optimality based on the power self-sufficiency rate, the power selling rate, and the operation rate. Based on the evaluated value, the optimum degree of combination of the solar panel capacity and the storage battery capacity is displayed.
Therefore, the optimal combination of the solar panel capacity and the storage battery capacity can be known.
In other words, the solar panel capacity and the storage battery capacity need not be increased as much as possible, and while achieving a high degree of self-sufficiency, the solar panel 1 does not perform unnecessary power generation and uses the storage battery 2 without waste. It is desirable to do. Based on the above evaluation values, it is possible to know the combination of the solar panel capacity and the storage battery capacity that can obtain an optimum balance between a high self-sufficiency ratio, efficient power generation, and a high operation rate of the storage battery 2.

  The embodiment of the present invention has been described in detail above with reference to the drawings. However, the specific configuration is not limited to this embodiment, and design changes that do not depart from the gist of the present invention are not limited to this embodiment. Included in the invention.

For example, in the embodiment, a house is exemplified as a building to which the present invention is applied. However, the present invention can be applied to a building other than a house.
Further, in the embodiment, the case where a storage battery is newly installed by renovation has been described as an example. However, the power generation system evaluation method of the present disclosure is not limited to renovation, and the storage battery capacity and solar power are not limited to renovation but at the design stage. It can also be used when determining the panel capacity.
Further, in the embodiment, the all-electric house is exemplified as the type of the residence to be calculated, but the calculation object is not limited to this all-electric house. In addition, when evaluating in a house (house) of a type other than this all-electric house, it is preferable to search for a house of the same type as the house to be evaluated and download the data.
Furthermore, in embodiment, the example which used the actual measurement data of the house currently input into management data as power consumption amount, generated electric energy amount, and charge / discharge amount (model data) which the residence (building) of evaluation object assumed However, the present invention is not limited to this. For example, based on such actual measurement data, model data may be created in advance according to the region, family structure, floor area, etc., and input to a personal computer or the like.
In the embodiment, the energy saving standard of 2013 is used as information on the location of the house (building) to be estimated when creating model data from the assumed power consumption, generated power, and charge / discharge. Although the example using the area division by is shown, the present invention is not limited to this, and the name of the prefecture or the name of the municipality may be used.

1 Solar panel (photovoltaic generator)
2 Storage battery 4 Measuring device 5 Management server E Commercial power supply H, H1,..., HX Housing (building)
MV Electric vehicle N Communication network PC Personal computer (power generation system evaluation device)
SC display screen

Claims (9)

A power generation system evaluation method for evaluating the optimum degree of combination of the capacity of a photovoltaic power generation device and a storage battery capacity with respect to the power consumption of a building,
Capacity condition input step for inputting capacity conditions of the photovoltaic power generation apparatus capacity and the storage battery capacity in the building to be evaluated;
A power condition input step for inputting the power consumption amount, the power sale power amount, the generated power amount, the charge amount and the discharge amount assumed in the building to be evaluated,
Based on each of the input conditions, a power self-sufficiency ratio that is a ratio of the amount of power other than the assumed power purchase amount in the assumed power consumption amount, and the assumed power sale in the assumed power generation amount. Obtaining a power selling rate that is a ratio of power capacity and an operating rate that is a ratio of the assumed discharge amount occupying the storage battery capacity, and further, the power self-sufficiency rate, the power selling rate, and the operating rate. An evaluation value calculation step for obtaining an evaluation value to be evaluated based on the optimality,
A power generation system evaluation method comprising: The power generation system evaluation method according to claim 1,
The said evaluation value is a power generation system evaluation method calculated | required as a value which is proportional to the said electric power self-sufficiency self-sufficiency rate and an operating rate, and inversely proportional to the said electric power selling rate. In the power generation system evaluation method according to claim 2,
The value obtained by subtracting the power selling rate from 1 is the solar self-consumption rate,
The evaluation value is a power generation system evaluation method obtained by calculating the power self-sufficiency rate × the operating rate × the solar self-consumption rate. In the electric power generation system evaluation method of any one of Claims 1-3,
The power self-sufficiency self-sufficiency rate is a power generation system evaluation method which is obtained by dividing a value obtained by adding the assumed discharge amount to the self-consumption power amount by the assumed power consumption amount. In the electric power generation system evaluation method of any one of Claims 1-4,
The power condition input step includes:
Each of a plurality of existing buildings, data of building specifications including the output capacity of the photovoltaic power generation device, the presence or absence of the storage battery, and the capacity thereof, regional data of each building, resident configuration data of each building, and each building A data input step of associating the power data measured during a predetermined period of time with each building and inputting the data into a database;
An extraction step of extracting data for trial calculation including the power data of the plurality of buildings according to the location and resident configuration of the building to be evaluated from the data input to the database;
Based on the extracted power data for trial calculation, the amount of power consumption, the amount of generated power, and the amount of power sold for a predetermined period according to the specifications of the building to be evaluated are obtained. Obtaining the estimated power consumption, the assumed generated power amount, and the assumed sold power amount based on the power amount, the sold power amount and the capacity condition;
A power generation system evaluation method comprising: In the electric power generation system evaluation method of Claim 5,
In the data input step, the power data is a power generation system evaluation method in which predetermined time data measured every predetermined time and predetermined period data stored as the predetermined period data are input to the database. In the power generation system evaluation method according to claim 5 or 6,
In the extraction step, each power data of the building selected based on the median value of the total power consumption is extracted from the building to be estimated, the area classification in which it is located, and the building extracted according to the resident composition. Power generation system evaluation method. In the electric power generation system evaluation method of any one of Claims 1-7,
In the device condition input step, a power generation system evaluation method in which a storage battery capacity of an electric vehicle is included as the storage battery capacity. A power generation system evaluation device that includes an input unit, a calculation unit, and a display unit, and evaluates and displays the optimum degree of combination of the photovoltaic power generation device capacity and the storage battery capacity with respect to the power consumption of the building,
The computing unit is
The capacity conditions of the solar power generation device capacity and the storage battery capacity in the evaluation target building input from the input unit, the power consumption amount, the power sale power amount, the power generation power amount, the charge amount assumed in the evaluation target building, and Based on the discharge amount, the power self-sufficiency rate, which is the ratio of the amount of power other than the assumed purchased power amount in the assumed power consumption amount, and the ratio of the assumed power sale amount in the assumed generated power amount And an operation rate that is a ratio of the assumed discharge amount in the storage battery capacity, and further, based on the power self-sufficiency rate, the power sale rate, and the operation rate. Obtain an evaluation value to evaluate the optimum degree,
A power generation system evaluation apparatus that displays an optimum degree of combination of the solar power generation apparatus capacity and the storage battery capacity based on the obtained evaluation value.