JP6400403B2 - Contract power selection device, contract power selection method, and contract power selection program - Google Patents

Description

  Embodiments described herein relate generally to a contract power selection device, a contract power selection method, and a contract power selection program.

  Liberalization of electricity retail is under consideration. However, in the conventional technology, there are cases where it is not possible to reduce the electricity bill in response to the liberalization of retail electricity.

Japanese Patent Laid-Open No. 06-276681 JP 2004-112869 A JP 2011-83084 A JP 2011-200040 A

  The problem to be solved by the present invention is to provide a contract power selection device, a contract power selection method, and a contract power selection program that can select contract power that reduces the electricity bill.

  The contract power selection apparatus according to the embodiment includes a calculation unit and a selection unit. The calculation unit calculates, for a plurality of contract powers, an electricity charge including a basic charge determined according to the contract power based on the usage mode of power in the target facility and the contract power indicating the upper limit of the purchased power. The selection unit selects contract electric power with a relatively low electric charge from a plurality of contract electric power based on the calculated electric charge.

The figure of the contract electric power selection system in an embodiment. The figure of the controlled object in an embodiment. The figure which shows operation | movement of the calculation part and selection part in embodiment. The figure which shows operation | movement of the calculation part and control part in embodiment. The figure of the individual used by the genetic algorithm in an embodiment. The figure which shows the genetic algorithm in embodiment.

Hereinafter, a contract power selection apparatus, a contract power selection method, and a contract power selection program according to an embodiment will be described with reference to the drawings.
FIG. 1 is a diagram of a contract power selection system 1 in the embodiment. The contract power selection system 1 includes a target facility 100 and a contract power selection device 200. There may be a plurality of target facilities 100. The contract power selection apparatus 200 may be plural.

  The target facility 100 is a facility that includes a control target. The control target is a target controlled by the contract power selection apparatus 200. The target facility 100 is, for example, a house. The target facility 100 may be a housing complex. When the target facility 100 is a house, the contract power selection system 1 is a home energy management system (HEMS).

 In FIG. 1, the target facility 100 includes a watt-hour meter 101, a distribution board 102, an air conditioner 103, a lighting device 104, a storage battery 105, a PCS 106 (Power Conditioning System), A photovoltaic power generation apparatus 107 (PV: Photovoltaics), a PCS 108, a fuel cell 109 (FC: Fuel Cell), a PCS 110, a gateway 111, and a terminal T are provided. Hereinafter, the air conditioner 103 and the lighting device 104 are collectively referred to as “load LD”.

  The watt hour meter 101 outputs information on the amount of power to the database 300 via the gateway 111. The gateway 111 is a home gateway when the target facility 100 is a house. The gateway 111 is a gateway of a local network of an apartment energy management system (MEMS) when the target facility 100 is an apartment house.

The distribution board 102 outputs information on the operating state of the load LD to the database 300 via the gateway 111.
The air conditioner 103 outputs information on the operating state of the air conditioner 103 to the database 300 via the gateway 111. The lighting device 104 outputs information on the operating state of the lighting device 104 to the database 300 via the gateway 111.

  The storage battery 105 outputs information on the operating state of the storage battery 105 to the database 300 via the PCS 106 and the gateway 111. The solar power generation device 107 outputs information on the operating state of the solar power generation device 107 to the database 300 via the PCS 108 and the gateway 111. The fuel cell 109 outputs information on the operating state of the fuel cell 109 to the database 300 via the PCS 110 and the gateway 111.

  The terminal T operates in response to an operation by the user U (customer). The terminal T outputs the operation history information to the database 300 via the gateway 111. The terminal T may output the operation history information to the database 300 without going through the gateway 111. The terminal T is, for example, a portable information device or a personal computer.

  The database 300 includes power demand information of the target facility 100, power consumption information, hot water supply demand information, operating state information such as a load LD, remaining charge information and charge / discharge power information of the storage battery 105, and a solar power generation device. The power generation amount information 107 and the hot water storage amount information of the hot water tank supplied from the fuel cell 109 are acquired via the gateway 111.

  The database 300 includes power demand information of the target facility 100, power consumption information, hot water supply demand information, operating state information such as a load LD, remaining charge information and charge / discharge power information of the storage battery 105, and a solar power generation device. The power generation amount information 107 and the hot water storage amount information of the hot water tank supplied from the fuel cell 109 are stored.

  The database 300 stores contract power information. The contract power information is information representing the upper limit of power purchased in a predetermined period according to the usage mode of power in the target facility 100. The predetermined period (time slot) may be 30 minutes, or may be shorter (instantaneous) than 30 minutes. The contract power may be expressed as power, or may be expressed as a voltage value or a current value. The database 300 may be distributed to a plurality of server devices by a cloud system. For example, the database 300 may be distributed to a plurality of server devices for each target facility 100.

  The electricity rate database 400 stores an electricity rate table presented by the power retailer A1. The electricity rate database 400 may store a plurality of electricity rate tables for more power retailers. The electricity tariff includes an electricity tariff plan for each power retailer. The plan for the electricity charge is represented by, for example, the unit price of the electricity charge for the purchased power every predetermined period. For example, an electricity bill plan is represented by the unit price of purchased electricity for every 30 minutes. The electricity tariff may be a relational database. The electricity tariff may be changed once a day to several months.

  The contract power selection apparatus 200 includes a prediction unit 201, a storage unit 202, a calculation unit 203, a selection unit 204, an interface 205, and a control unit 206.

  The prediction unit 201 includes power demand information of the target facility 100, power consumption information, hot water supply demand information, operating state information such as the load LD, remaining charge information and charge / discharge power information of the storage battery 105, and solar power generation. The power generation amount information of the apparatus 107 and the hot water storage amount information of the hot water tank that acquires the exhaust heat from the fuel cell 109 are acquired from the database 300. The prediction unit 201 acquires weather forecast information from the weather company 500.

  The prediction unit 201 predicts the power demand on the target facility 100 in the target facility 100. The target date is a date (calculation date) for calculating the peak of purchased power. The prediction unit 201 may predict the power demand on the target day multiple times a day. The prediction unit 201 predicts the power demand on the target day based on, for example, weather forecast information, past power demand, and a neural network. For example, the prediction unit 201 may group past power demands for a plurality of target facilities 100 (customers), and predict power demand on the target date based on an average demand fluctuation model for each group. .

  The prediction unit 201 predicts the demand for hot water supply on the target day in the target facility 100. The prediction unit 201 may predict the demand for hot water supply on the target day multiple times a day. The prediction unit 201 predicts the demand for hot water supply on the target day based on, for example, calendar information.

  The prediction unit 201 predicts the power generation amount of the solar power generation device 107 on the target day in the target facility 100. For example, the prediction unit 201 predicts the power generation amount of the solar power generation device 107 on the target day based on the statistical correlation of the power generation amount of the solar power generation device 107 at different past times. For example, the prediction unit 201 may predict the power generation amount of the solar power generation device 107 on the target day based on the statistical correlation of the power generation amount of the solar power generation device 107 at different installation positions in the past.

  The storage unit 202 stores information representing the contract power calculation period. The contract power calculation period is a period including the target date. The storage unit 202 stores model information (constraint conditions) of a control target in the target facility 100. The model information of the control target is information representing the relationship between the input information to the component to be controlled and the output information from this component. The model information to be controlled is information representing the relationship between the output information from the component to be controlled and the input information to other components. The model information to be controlled may be expressed by a mathematical formula.

  FIG. 2 is a diagram of a control target in the embodiment. In FIG. 2, the components to be controlled are the power system PW, the fuel cell unit FU, the storage battery 105, the PCS 106, the solar power generation device 107, the PCS 108, and the load LD. The fuel cell unit FU includes a fuel cell 109, a PCS 110, an auxiliary boiler 114, a backflow prevention heater 112, and a hot water tank 113.

t is a variable representing time [h]. F (t) is a variable representing the gas supply amount [kcal / h]. F _FC (t) is a variable representing the gas supply amount [kcal / h] to the fuel cell 109. F _B (t) is a variable representing the gas supply amount [kcal / h] to the auxiliary boiler 114.

P _C (t) is a variable representing purchased power [kW] from the power system PW. P _C (t) is a variable representing the power selling power [kW] when it is a negative value. P _PV (t) is a variable representing the power generation amount [kW] of the solar power generation device 107. S (t) is a variable that represents the remaining charge [kWh] of the storage battery 105. P _SB (t) is a variable representing charging power [kW] of the storage battery 105. P _SB (t) is a variable representing discharge power [kW] when it is a negative value. P _D (t) is a variable representing the power demand [kW] of the load LD.

P _FC (t) is a variable representing the effective power [kW] of the power generation amount of the fuel cell 109. P _H (t) is a variable representing the power consumption [kW] of the backflow prevention heater 112. Φ _H (t) is a variable representing the calorific value [kcal / h] of the backflow prevention heater 112. Φ _FC (t) is a variable representing the amount of exhaust heat [kcal / h] of the fuel cell 109. H (t) is a variable representing the hot water storage amount [kcal] of the hot water storage tank 113. Φ _ST (t) is a variable representing the hot water supply amount [kcal / h] from the hot water storage tank 113. Φ _B (t) is a variable representing the hot water supply amount [kcal / h] from the auxiliary boiler 114. Φ _D (t) is a variable representing hot water supply demand [kcal / h].

The model information (constraint condition) to be controlled is expressed by Expression (1) to Expression (9). The gas supply amount F (t) is divided into a supply F _FC (t) to the solar power generation device 107 and a supply F _B (t) to the auxiliary boiler 114.

F (t) = F _FC (t) + F _B (t) (1)

The fuel cell 109 outputs the power generation amount P _FC (t) to the distribution line LN via the PCS 110 according to the gas supply amount F _FC (t). In equation (2), a is a coefficient determined from the efficiency of the fuel cell 109. b is a coefficient determined from the efficiency of the fuel cell 109.

P _FC (t) = aF _FC (t) + b (2)

The fuel cell 109 generates heat according to the gas supply amount F _FC (t), and supplies the exhaust heat amount Φ _FC (t) to the hot water storage tank 113. In Expression (3), α is a coefficient determined from the efficiency of the fuel cell 109. β is a coefficient determined from the efficiency of the fuel cell 109.

Φ _FC (t) = αF _FC (t) + β (3)

The backflow prevention heater 112 generates heat according to the power consumption P _H (t) and supplies the heat generation amount Φ _H (t) to the hot water tank 113. The backflow prevention heater 112 can prevent the power generation amount P _FC (t) of the fuel cell 109 from flowing back into the power system PW. The auxiliary boiler 114 adds the hot water supply amount Φ _B (t) to the hot water supply amount Φ _ST (t) from the hot water storage tank 113 to obtain the hot water supply demand Φ _D (t).

As shown in the equation (4), the hot water storage tank 113 corresponds to the exhaust heat amount Φ _FC (t) of the fuel cell 109, the heat generation amount Φ _H (t) of the backflow prevention heater 112, and the hot water supply Φ _ST (t). The hot water storage amount H (t) is increased or decreased. The hot water storage efficiency r is determined according to the amount of heat lost due to heat dissipation or the like. The calculation unit 203 calculates the future hot water storage amount of the hot water storage tank 113 based on the past hot water storage amount of the hot water storage tank 113 as shown in Expression (4).

rH (t−1) + Φ _FC (t) + Φ _H (t) = H (t) + Φ _ST (t) (4)

The hot water storage tank 113 has a capacity restriction. H _min is a lower limit value of the capacity of the hot water tank 113. H _max is an upper limit value of the capacity of the hot water tank 113.

H _min (t) ≦ H (t) ≦ H _max (t) (5)

Charging / discharging of the storage battery 105 is controlled by the PCS 106. The storage battery 105 supplies charging power P _SB (t) to the load LD via the PCS 106. The remaining charge S (t) of the storage battery 105 increases or decreases according to the charge power P _SB (t) of the storage battery 105. The balance between supply and demand of electric power is expressed by equation (6).

P _C (t) + P _PV (t) + P _FC (t) + P _SB (t) = P _D (t) + P _H (t) (6)

Gas supply amount P _FC (t) to the fuel cell 109, charging power P _SB (t) of the storage battery 105, power demand P _D (t) of the load LD, and power consumption P _H ( The relationship with t) is expressed by equations (7) and (8).

P _FC (t) + P _SB (t) ≦ P _D (t) + P _H (t) (7)

P _H (t) ≦ P _FC (t) (8)

The constraint condition of the capacity of the storage battery 105 is expressed by Expression (9). S _min is a lower limit value of the capacity of the storage battery 105. S _max is an upper limit value of the capacity of the storage battery 105.

S _min (t) ≦ S (t) ≦ S _max (t) (9)

  Returning to FIG. 1, the description of the contract power selection system 1 will be continued. The calculation unit 203 acquires contract power information from the database 300. The calculation unit 203 calculates an electricity rate for a plurality of contracted powers based on the usage mode of power in the target facility and the contracted power information. Electricity charges include basic charges and pay-as-you-go charges. The basic charge is a fixed charge determined according to the contract power. The basic fee may be determined every predetermined period. For example, the basic fee may be set every 30 minutes. The metered rate is determined according to the power purchased during a predetermined period and the unit price of the purchased electricity. For example, the pay-per-use charge is determined according to the power purchased for 30 minutes and the electricity charge for the purchased power for 30 minutes.

The calculation unit 203 calculates the schedule (plan) of the power generation amount P _FC (t) of the fuel cell 109 based on the power demand so that the electricity bill is reduced under the condition that the peak of purchased power is equal to or less than the contract power. Then, a schedule of the charge / discharge power amount P _SB (t) of the storage battery 105 is calculated. The calculation unit 203 includes at least one of hot water supply demand, the power generation amount of the solar power generation device 107, the unit price of purchased electricity, the unit price of the gas rate, and the purchase price of the power generation amount of the solar power generation device 107. Based on the above, the schedule of the power generation amount P _FC (t) of the fuel cell 109 and the schedule of the charge / discharge power amount P _SB (t) of the storage battery 105 may be calculated so that the electricity rate is reduced.

For example, the calculation unit 203 calculates the schedule of the power generation amount P _FC (t) of the fuel cell 109 and the schedule of the charge / discharge power amount P _SB (t) of the storage battery 105 by a genetic algorithm. Note that the calculation unit 203 may calculate the schedule of the power generation amount P _FC (t) of the fuel cell 109 and the schedule of the charge / discharge power amount P _SB (t) of the storage battery 105 by a method other than the genetic algorithm. .

  The calculation unit 203 may calculate an electricity rate for each contract power based on the prediction of power demand. The calculation unit 203 may calculate an electricity bill for each contracted power based on the prediction of the demand for hot water supply. That is, the calculation unit 203 calculates the charging / discharging schedule of the storage battery 105 based on at least one of prediction of power demand, prediction of demand for hot water supply, and prediction of power generation amount of the solar power generation device 107. May be. The calculation unit 203 notifies the selection unit 204 of information indicating optimal scheduling. Optimal scheduling is, for example, scheduling that provides the lowest price for electricity.

  The calculation unit 203 calculates a charge / discharge schedule of the fuel cell 109 based on at least one of prediction of power demand, prediction of demand for hot water supply, and prediction of power generation amount of the solar power generation device 107. Also good. The calculation unit 203 calculates the amount of power to be purchased from the power system PW based on at least one of prediction of power demand, prediction of demand for hot water supply, and prediction of power generation amount of the solar power generation device 107. Also good. The calculation unit 203 calculates the amount of power to be sold to the power system PW based on at least one of prediction of power demand, prediction of demand for hot water supply, and prediction of power generation amount of the solar power generation device 107. May be.

  The selection unit 204 selects contract power with a relatively low electricity rate from the contract power information stored in the database 300. The selection unit 204 selects the optimum contract power from a plurality of contract powers based on the information indicating the optimum scheduling calculated by the calculation unit 203. The optimum contract power is, for example, contract power at which the electricity rate is the cheapest.

  The interface 205 acquires various information from the selection unit 204. The various information is, for example, information representing contract power selected by the selection unit 204. The various types of information may be, for example, information representing an electricity bill stored in the electricity bill database 400. The various information may be, for example, information indicating a charging / discharging schedule of the storage battery 105 or information indicating a power generation schedule of the fuel cell 109. The interface 205 presents various information to the user U. The interface 205 is a display device, for example.

  The interface 205 receives an operation by the user U. The interface 205 is, for example, a touch panel or a keyboard. The interface 205 accepts an operation for designating contract power with which the user U contracts with a power retailer. The interface 205 accepts an operation that permits execution of control using the electricity rate table. The interface 205 receives schedule correction information so that the calculation unit 203 can calculate a schedule desired by the user U.

  Based on the contract power selected by the selection unit 204, the control unit 206 controls the power usage mode of the target facility 100 so that the peak of purchased power is equal to or less than the contract power. That is, the control unit 206 outputs the driving instruction or the stop instruction and the output target value to the control target in the target facility 100 via the gateway 111 based on the schedule calculated by the calculation unit 203. Control targets are, for example, the storage battery 105, the solar power generation device 107, and the fuel cell 109. The output target value may be represented by either active power or reactive power. The control unit 206 may output the operation instruction or the stop instruction and the output target value at a constant time period.

  FIG. 3 is a diagram illustrating operations of the calculation unit 203 and the selection unit 204 in the embodiment. For example, the calculation unit 203 and the selection unit 204 execute the operation illustrated in FIG. 3 at a timing of once every several months. The calculation unit 203 and the selection unit 204 may execute the operation illustrated in FIG. 3 at a timing based on an operation by the user U.

The calculation unit 203 acquires information representing the contract power calculation period from the storage unit 202. The calculation unit 203 determines the first day of the contract power calculation period as the calculation date (step S101).
The calculation unit 203 acquires an electricity rate table from the electricity rate database 400. The calculation unit 203 acquires the contract power information from the database 300 (step S102).

The calculation unit 203 calculates an electricity bill for a predetermined period (step S103).
The calculation unit 203 acquires power demand information, hot water supply demand information, and power generation amount information (actual data) of the solar power generation device 107 for each date (step S104).
The calculation unit 203 performs optimal scheduling (step S105).
The calculation unit 203 calculates the peak of purchased power for a predetermined period (time slot) in which optimal scheduling has been executed (step S106).

The calculation unit 203 determines whether the calculation date is within the contract power calculation period (step S107).
When the calculation date is not within the contract power calculation period (step S107: NO), the selection unit 204 selects the contract power that provides the lowest electricity bill (step S108).

The interface 205 presents information representing the contract power selected by the selection unit 204 to the user U (step S109). The user U can perform the procedure for purchasing the power retailer A1 power with reference to the presented contract power.
In step S107, when the calculation date is within the contract power calculation period (step S107: YES), the calculation unit 203 determines the next day as the calculation date.

  FIG. 4 is a diagram illustrating operations of the calculation unit 203 and the control unit 206 in the embodiment. The calculation unit 203 and the control unit 206 perform the operation shown in FIG. 4 at a timing of once every day to several months, for example. The calculation unit 203 and the selection unit 204 execute the operation illustrated in FIG. 3 at the timing when the power demand information, the hot water supply demand information, and the power generation amount information of the solar power generation device 107 are predicted.

The calculation unit 203 acquires power demand information, hot water supply demand information, and power generation amount information (actual data) of the solar power generation device 107 for each date (step S201).
The prediction unit 201 predicts the power demand on the target day, the power demand on the target day, and the power generation amount of the solar power generation device 107 on the target day (step S202).

The calculation unit 203 performs optimal scheduling. For example, the calculation unit 203 sets the schedule of the power generation amount P _FC (t) of the fuel cell 109 and the charge / discharge power amount of the storage battery 105 so that the electricity rate is reduced while keeping the peak of purchased power below the contract power. The schedule of P _SB (t) is calculated. Further, for example, the calculation unit 203 schedules the power generation amount P _FC (t) of the fuel cell 109 and the charge / discharge power amount P _SB (t) of the storage battery 105 so that the purchase amount of the power generation becomes high. Are calculated (step S203).

  The interface 205 presents a charging / discharging schedule of the storage battery 105. The interface 205 presents a power generation schedule of the fuel cell 109 (step S204). The user U can confirm the charge / discharge schedule of the storage battery 105 and the power generation schedule of the fuel cell 109.

  The control unit 206 determines whether or not the user U has permitted execution of the schedule (step S205). When the user U does not permit execution of the schedule (step S205: NO), the control unit 206 returns the process to step S201. When the user U permits execution of the schedule (step S205: YES), the control unit 206 sends the driving instruction or stop instruction and the output target value to the gateway 111 based on the schedule calculated by the calculation unit 203. To the control target in the target facility 100. The operation instruction is, for example, a charge / discharge instruction or a power generation instruction (step S206). The control unit 206 may output the operation instruction or the stop instruction and the output target value at a constant time period.

  By step S202 and step S203, the contract power selection apparatus 200 sets the power demand and supply schedule based on the predictions of the power demand, the hot water supply demand, and the power generation amount of the solar power generation apparatus 107 in a set period. Can stand.

FIG. 5 is a diagram of individuals used in the genetic algorithm in the embodiment. The calculation unit 203 may calculate the schedule of the power generation amount P _FC (t) of the fuel cell 109 and the schedule of the charge / discharge power amount P _SB (t) of the storage battery 105 by a genetic algorithm. The genes used in the genetic algorithm include the operating state SP _C (t) of the fuel cell 109, the power generation amount P _FC (t) of the fuel cell 109, and the charge / discharge power amount P _SB (t) of the storage battery 105. It is. If the operating state SP _C (t) is 1, the operating state SP _C (t) represents the operating state. The operating state SP _C (t) indicates a stopped state when the value is 0. The individuals used in the genetic algorithm are the daily operation schedule of the storage battery 105 and the daily operation schedule of the fuel cell 109. A plurality of individuals form a population (generation) in the genetic algorithm.

  The model information (constraint condition) to be controlled is expressed by Expression (10) to Expression (12). Equation (10) represents the fitness. The fitness is maximized by a genetic algorithm.

Fit is an evaluation function (fitness) of the utility bill. The degree of conformity is, for example, the cost “g (P _FC ,) due to discontinuous operation of the controlled object in a monotonically increasing function f (C) (positive value) with the balance C of the utility cost per day as a variable. P _SB ) ”(positive value) is the reciprocal of the added value. The reason why the added value is the reciprocal is that, when the power generation amount of the photovoltaic power generation apparatus 107 greatly exceeds the power demand of the target facility 100, the balance C of the utility cost may be negative. That is, the reason why the added value is the reciprocal is to increase the fitness Fit as the monotonically increasing function f (C) decreases.

  The utility cost is determined according to the unit price for purchasing the amount of power generated by the solar power generation apparatus 107 and the unit price for the metered rate. The balance C of the utility cost per day is expressed by equation (11).

_CE is the unit price [yen / kWh] of the electricity rate when P _C (t) is a positive value. _CE is the unit price [yen / kWh] for purchasing power generated by the solar power generation device 107 when P _C (t) is 0 or less. _CF is a unit price [yen / kcal] of the gas rate.

The cost “g (P _FC , P _SB )” due to the discontinuous operation of the control target is expressed by Expression (12). The right side of Expression (12) represents the output change of the fuel cell 109 and the storage battery 105. The cost is lower as the output change is smaller.

g (P _FC , P _SB ) = w ₁ | P _FC (t) −P _FC (t−1) | + w ₂ | P _SB (t) −P _SB (t−1) | (12)

“| P _FC (t) −P _FC (t−1) |” is the absolute value of the difference between the power generation amount of the fuel cell 109 at time t and the power generation amount of the fuel cell 109 at time (t−1). Represents. w1 is a weighting coefficient. “| P _SB (t) −P _SB (t−1) |” is the absolute value of the difference between the charge / discharge amount of the storage battery 105 at time t and the charge / discharge amount of the storage battery 105 at time (t−1). Represents. w2 is a weighting coefficient.

  The calculation unit 203 is based on the electric power demand, the hot water supply demand, the power generation amount of the solar power generation device 107, the unit price of the electricity rate, the unit price of the gas rate, and the unit price for purchasing the power generated by the solar power generation device 107. Repeat genetic algorithms such as mutation, crossover, and selection.

The calculation unit 203 includes the active power P _FC (t) of the power generation amount of the fuel cell 109 and the reactive power Q of the power generation amount of the fuel cell 109 so that the electricity bill of purchased power is reduced in the utility bill C. _FC (t) and charging power P _SB (t) of the storage battery 105 are calculated. In addition, the calculation unit 203 calculates the effective power P _FC (t) of the power generation amount of the fuel cell 109 and the invalidity of the power generation amount of the fuel cell 109 so that the purchase amount of the power generation amount in the utility bill C is high. Electric power Q _FC (t) and charging power P _SB (t) of storage battery 105 are calculated.

FIG. 6 is a diagram illustrating a genetic algorithm in the embodiment.
The calculation unit 203 generates an initial population. The calculation unit 203 randomly generates n individuals that satisfy the constraint conditions. The calculation unit 203 may generate n individuals that satisfy the constraint conditions based on past performance values. If the individual does not satisfy the constraint condition, the calculation unit 203 bit-inverts the gene so that the constraint condition is satisfied (step S301).

The calculation unit 203 calculates the fitness of each individual and the average of the fitness in the generation to which each individual belongs (hereinafter referred to as “average fitness”) (step S302).
The calculation unit 203 determines whether or not the calculated average fitness is equal to or less than a predetermined value ε than the average fitness of the two previous generations from that generation. Further, the calculation unit 203 determines whether or not the number of generations is equal to or greater than the maximum number of generations (step S303).

When the calculated average fitness is a predetermined value ε or less than the average fitness of the two previous generations from that generation, or when the number of generations is the maximum number of generations or more (step S303: YES), the calculation unit 203 The determination result by the genetic algorithm is output to the control unit 206. The determination result represents the schedule of the power generation amount P _FC (t) of the fuel cell 109 and the schedule of the charge / discharge power amount P _SB (t) of the storage battery 105 (step S304).

  When the calculated average fitness is not less than or equal to the predetermined value ε than the average fitness of the two previous generations, and when the number of generations is not equal to or greater than the maximum number of generations (step S303: NO), the calculation unit 203 Indulge individuals that do not meet the conditions. In addition, when the number of individuals is equal to or greater than the predetermined number, the calculation unit 203 selects an individual having a low fitness level until the number of individuals is less than the predetermined number (step S305).

When the number of individuals becomes less than a predetermined number, the calculation unit 203 causes the individuals with high fitness to proliferate (step S306).
The calculation unit 203 randomly pairs individuals with respect to individuals having a predetermined ratio (crossover rate) with respect to the number of all individuals. The calculation unit 203 performs a crossover process on the paired individuals. The crossover process is a process of randomly selecting a gene for each paired individual and performing a single point crossover (step S307).

The calculation unit 203 randomly selects individuals having a predetermined ratio (mutation rate) with respect to the number of all individuals. The calculation unit 203 selects a gene of the selected individual at random. The calculation unit 203 performs a mutation process on the selected individual. The mutation process is a process of inverting the bit of the selected gene (step S308).
The calculation unit 203 increases the number of generations by one generation (step S309). The calculation unit 203 returns the process to step S302.

  As described above, the contract power selection apparatus 200 according to the embodiment includes the calculation unit 203 and the selection unit 204. The calculation unit 203 calculates, for a plurality of contract powers, an electricity charge including a basic charge determined according to the contract power, based on the power usage in the target facility 100 and the contract power representing the upper limit of the purchased power. The selection unit 204 selects contract electric power with a relatively low electric charge from a plurality of contract electric power based on the calculated electric charge.

  The contract power selection method according to the embodiment is a contract power selection method in the contract power selection apparatus 200, and includes a calculation step and a selection step. In the calculating step, the calculation unit 203 calculates an electric charge including a basic charge determined according to the contract electric power based on the usage mode of the electric power in the target facility 100 and the contract electric power indicating the upper limit of the purchased electric power to a plurality of contracts. Calculate for power. In the selecting step, the selection unit 204 selects contract power with a relatively low power charge from a plurality of contract power based on the calculated power charge.

  The contract power selection program according to the embodiment causes a computer to execute a calculation procedure and a selection procedure. In the calculation procedure, the computer calculates an electric charge including a basic charge determined according to the contract power for a plurality of contract power based on the usage mode of power in the target facility 100 and the contract power indicating the upper limit of the purchased power. calculate. In the selecting procedure, the computer selects contract power with a relatively low electricity price from a plurality of contract power based on the calculated electricity price.

  In this configuration, the selection unit 204 selects contract electric power with a relatively low electric charge from a plurality of contract electric power based on the calculated electric charge. Thereby, the contract power selection apparatus 200 can select the contract power that reduces the electricity bill.

  Conventionally, the contract power for determining the electricity rate was regarded as a constant. That is, conventionally, the contract power for determining the electricity rate has not been a variable of the evaluation function. With the contract power selection apparatus 200 according to the embodiment, the user U can reduce the utility cost without taking a troublesome procedure. Moreover, the user U can purchase electric power with the unit price of the electric charge of cheaper purchased electric power, when the contract electric power selection apparatus 200 performs electric power transaction.

  The prediction unit 201 predicts the power demand in the target facility 100. The calculation unit 203 calculates an electricity bill for each contracted power based on the prediction of power demand. The prediction unit 201 may predict the demand for power based on the weather forecast. The prediction unit 201 may predict the demand for hot water supply in the target facility 100. The calculation unit 203 may calculate an electricity bill for each contracted power based on the prediction of the demand for hot water supply. The control unit 206 controls the usage mode of power so that the purchased power is less than or equal to the contract power. The interface 205 presents the selected contract power.

  According to at least one embodiment described above, by having the selection unit 204 that selects contract power with relatively low electricity charges from a plurality of contract electricity based on the calculated electricity charges, Contract power to be reduced can be selected.

  As mentioned above, although some embodiment of this invention was described, these embodiment is shown as an example and is not intending limiting the range of invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the invention described in the claims and the equivalents thereof.

DESCRIPTION OF SYMBOLS 1 ... Contract electric power selection system, 100 ... Target facility, 101 ... Electricity meter, 102 ... Distribution board, 103 ... Air conditioning equipment, 104 ... Illumination equipment, 105 ... Storage battery, 106 ... PCS, 107 ... Solar power generation device, 108 DESCRIPTION OF SYMBOLS ... PCS, 109 ... Fuel cell, 110 ... PCS, 111 ... Gateway, 112 ... Backflow prevention heater, 113 ... Hot water storage tank, 114 ... Auxiliary boiler, 200 ... Contract power selection device, 201 ... Prediction unit, 202 ... Storage unit, DESCRIPTION OF SYMBOLS 203 ... Calculation part 204 ... Selection part 205 ... Interface, 206 ... Control part, 300 ... Database, 400 ... Electricity rate database, 500 ... Meteorological company, 600 ... Gas company, 700 ... Wholesale electric power market, A1 ... Electric power retailer , FU ... Fuel cell unit, LD ... Load, LN ... Distribution line, PT ... Power receiving point, PW ... Power system, T ... Terminal, U ... User

Claims (7)

Based on usage of power in a target facility equipped with a fuel cell or storage battery and contract power representing the upper limit of purchased power, an electricity charge including a basic charge determined according to the contract power is calculated for a plurality of the contract power A calculating unit to
Based on the calculated electricity price, a selection unit that selects the contracted power at which the electricity price is relatively cheap from the plurality of contracted powers;
A prediction unit for predicting the demand for the electric power in the target facility,
The calculating unit is configured such that the electricity charge per contract power is the cheapest, the fuel cell or contract power you calculate a schedule for control of the battery for each of the contract demand, based on the predicted demand of the power Selection device. The contract power selection apparatus according to claim 1 , wherein the prediction unit predicts a demand for the power based on a weather forecast. The prediction unit predicts demand for hot water supply in the target facility,
The contract power selection apparatus according to claim 1 , wherein the calculation unit calculates the electricity rate for each contract power based on a prediction of demand for the hot water supply. The contract power selection apparatus according to any one of claims 1 to 3 , further comprising a control unit that controls a usage mode of the power so that the purchased power is equal to or less than the contract power. The contract power selection apparatus according to any one of claims 1 to 4 , further comprising an interface that presents the selected contract power. A contract power selection method in the contract power selection device,
Based on usage of power in a target facility equipped with a fuel cell or storage battery and contract power representing the upper limit of purchased power, an electricity charge including a basic charge determined according to the contract power is calculated for a plurality of the contract power And steps to
Selecting the contract power with a relatively low power price from the plurality of contract power based on the calculated power price;
Predicting the demand for the power at the target facility,
In the calculating step, the contract power for calculating the schedule of control of the fuel cell or the storage battery for each contract power based on the prediction of the demand for the power so that the electricity charge for each contract power is the lowest. Selection method. On the computer,
Based on usage of power in a target facility equipped with a fuel cell or storage battery and contract power representing the upper limit of purchased power, an electricity charge including a basic charge determined according to the contract power is calculated for a plurality of the contract power And the steps to
A step of selecting the contract power with a relatively low power charge from the plurality of contract power based on the calculated power charge;
Predicting the power demand at the target facility, and
In the calculating procedure, a schedule for controlling the fuel cell or the storage battery is calculated for each contract power based on a prediction of the demand for the power so that the electricity charge for each contract power is the lowest . Contract power selection program.

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