JP2014160399A - Solution search device, solution search method and program, schedule generating device, schedule generation method, program, and charging control system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain an appropriate solution satisfying a constraint while easily generating an individual as an initial solution.SOLUTION: An individual generation part 102 generates an individual which satisfies a temporary constraint which is a condition looser than a constraint. A generation calculation part 105 selects an individual on the basis of a probability based on an evaluation value calculated by an evaluation value calculation part 104, and generates a new individual which satisfies the temporary constraint by genetic manipulation. A condition changing part 106 changes the temporary constraint into a condition close to the constraint, when generation calculation part 105 executes calculation. A solution derivation part 107 derives a solution from the individual generated by the generation calculation part 105, after the temporary constraint becomes equal to the constraint.

Description

  The present invention relates to a solution search device, a solution search method and a program for searching for a solution that satisfies a constraint condition, a schedule generation device that generates a power control schedule for a facility including a secondary battery, a schedule generation method and a program, and a secondary battery The present invention relates to a charging control system that controls charging.

  In recent years, a technique for reducing power consumption using an energy management system (EMS) has been studied. In recent years, a technique for adjusting electric power in a home or a company using electric power of a secondary battery mounted on an electric vehicle has been studied. In these technologies, generally, an EV secondary battery is charged at night when the electricity bill is relatively inexpensive, and the EV secondary battery is discharged during a day when the electricity bill is relatively expensive. Adjustments are being made.

  Here, if a company or the like has multiple EVs and tries to reduce the electricity bill, if all EVs are charged at night, the peak power at night will increase, and it will be necessary to raise the contract power, resulting in electricity There is a problem that the bill becomes expensive.

  To solve this problem, Patent Document 1 discloses a technique for obtaining an appropriate charge / discharge pattern by performing mathematical optimization as a method for controlling charge / discharge of a large number of EVs.

  A genetic algorithm is known as a method of mathematical optimization. A genetic algorithm is a method that randomly generates multiple individuals that are solution candidates, performs a genetic operation on an individual of a certain generation, repeatedly executes a process of generating an individual of the next generation, and the last generation obtained This algorithm uses the individual with the highest appropriateness among the individuals. Here, the genetic operation refers to selection, mutation, and crossover operations. In the genetic algorithm, an individual having a higher appropriateness as a solution increases the probability of being a target of the genetic operation.

The selection operation is an operation of selecting one individual and copying the individual. The mutation operation refers to an operation of selecting one individual and changing a part of the individual. The crossover operation is an operation of selecting two individuals and exchanging a part thereof.
In this specification, the calculation for generating the next generation individual is referred to as generation calculation.

JP 2012-213316 A

However, as in the method disclosed in Patent Document 1, when searching for a solution using mathematical optimization, it is necessary to generate an initial solution (first generation individual in the genetic algorithm) that satisfies a constraint condition, There is a problem that it is difficult to generate an initial solution when the constraint condition is severe.
An object of the present invention is to provide a solution search device, a solution search method and program, a schedule generation device, a schedule generation method and program, and a charge control system that solve the above-described problems.

  The present invention has been made to solve the above-described problem, and is a solution search apparatus that searches for a solution that satisfies a constraint condition, and that generates an individual that satisfies a temporary constraint condition that is looser than the constraint condition. A generation unit, an evaluation value calculation unit that calculates an evaluation value for the individual using a predetermined evaluation function, and the individual is selected based on the probability based on the evaluation value calculated by the evaluation value calculation unit. A generation calculation unit that repeatedly executes a generation calculation that generates a new individual that satisfies the temporary constraint condition by genetic operation according to a genetic algorithm; and when the generation calculation unit executes the generation calculation, the temporary constraint condition is A condition change unit for changing to a condition close to the constraint condition, and after the temporary constraint condition becomes equal to the constraint condition, derive a solution from the individual generated by the generation calculation of the generation calculation unit Characterized in that it comprises a solution deriving unit.

  Further, in the present invention, the evaluation value calculation unit calculates a temporary evaluation function for deriving an evaluation value indicating a higher evaluation as the individual is closer to a value satisfying the constraint condition until the temporary constraint condition is equal to the constraint condition. Using the evaluation function to calculate an evaluation value for the individual after the temporary constraint condition is equal to the constraint condition, and the solution derivation unit is configured to calculate the evaluation value for the individual. Based on the evaluation value calculated by the calculation unit using the evaluation function, a solution is derived from the individual generated by the generation calculation of the generation calculation unit.

  In the present invention, the generation calculation unit executes the genetic operation within a range that does not violate at least one of the provisional constraint conditions.

  Further, in the present invention, the generation calculation unit, when performing a mutation operation in the genetic operation, a predetermined probability that a portion in which the evaluation value is likely to vary among the individuals becomes a target of the genetic operation is high. The genetic operation is performed based on the probability of.

  Further, the present invention provides a solution search method using a solution search apparatus for searching for a solution that satisfies a constraint condition, wherein the individual generation unit generates an individual that satisfies a temporary constraint condition that is a looser condition than the constraint condition. And an evaluation value calculation unit calculating an evaluation value for the individual using a predetermined evaluation function, and a generation calculation unit based on the probability based on the evaluation value calculated by the evaluation value calculation unit. A step of repeatedly executing a generation calculation for generating a new individual satisfying the provisional constraint condition by a genetic operation related to a genetic algorithm, a condition changing unit, and the generation calculation unit executing the generation calculation The temporary constraint condition is changed to a condition close to the constraint condition, and the solution derivation unit, after the temporary constraint condition becomes equal to the constraint condition, the generation of the generation calculation unit Characterized by a step of deriving a solution from an individual that is generated by the calculation.

  In addition, the present invention provides an evaluation value calculation for calculating an evaluation value for an individual using a predetermined evaluation function, an individual generation unit that generates an individual that satisfies a temporary constraint condition that is a condition looser than a predetermined constraint condition. Selecting the individual based on the probability based on the evaluation value calculated by the evaluation value calculation unit, and repeating generational generation to generate a new individual that satisfies the temporary constraint condition through a genetic operation related to a genetic algorithm A generation calculation unit to be executed, a condition change unit for changing the temporary constraint condition to a condition close to the constraint condition when the generation calculation unit has executed the generation calculation, and the temporary constraint condition is equal to the constraint condition This is a program for functioning as a solution derivation unit that derives a solution from an individual generated by the generation calculation of the generation calculation unit later.

  In addition, the present invention is a schedule generation device that generates a charging schedule for a secondary battery in a facility including a secondary battery, and the power that the facility receives from the power system per unit time is higher than a predetermined contract power Using an individual generation unit that generates an individual that satisfies the provisional constraint condition that does not exceed the provisional contract power, which is power, and an evaluation function that derives an evaluation value that indicates a higher evaluation as the electricity bill is smaller An evaluation value calculation unit for calculating an evaluation value for the individual, and selecting the individual based on a probability based on the evaluation value calculated by the evaluation value calculation unit, and performing the temporary constraint by a genetic operation according to a genetic algorithm A generation calculation unit that repeatedly executes generation calculation that generates a new individual that satisfies the condition, and when the generation calculation unit executes the generation calculation, the provisional contract power is A condition change unit that changes to a value close to about power, and the charge schedule is generated based on the individual generated by the generation calculation of the generation calculation unit after the provisional contract power becomes equal to the contract power And a solution deriving unit.

  Further, in the present invention, the evaluation value calculation unit indicates an evaluation value indicating a higher evaluation as the maximum value of power supplied from the power system to the facility per unit time is smaller until the provisional contract power becomes equal to the contract power. An evaluation value is calculated for the individual using a temporary evaluation function for deriving, and after the temporary contract power becomes equal to the contract power, an evaluation value is calculated for the individual using the evaluation function, and the solution The derivation unit derives a solution from the individual generated by the generation calculation of the generation calculation unit based on the evaluation value calculated by the evaluation value calculation unit using the evaluation function.

  Further, in the present invention, the facility includes a plurality of chargers that charge the secondary battery and the secondary battery, and the temporary constraint condition is that each of the chargers must not simultaneously charge a plurality of secondary batteries. The generation calculation unit performs an operation in units of the charger when performing a crossover operation or a mutation operation in the genetic operation.

  Further, in the present invention, the generation calculation unit, when performing a mutation operation in the genetic operation, the predetermined probability that the time period in which the electricity cost is low among the individuals is a target of the genetic operation is high Based on the above, the genetic operation is performed.

  Further, the present invention is a schedule generation method using a schedule generation device for generating a charging schedule of the secondary battery in the facility including the secondary battery, wherein the individual generation unit is connected to the power system in unit time. The step of generating an individual that satisfies the provisional constraint condition including the condition that the supplied power does not exceed the provisional contract power with a value higher than the predetermined contract power, and the evaluation value calculation unit has a smaller electricity cost. A step of calculating an evaluation value for the individual using an evaluation function for deriving an evaluation value indicating a high evaluation, and a generation calculation unit, based on the probability based on the evaluation value calculated by the evaluation value calculation unit, A step of selecting and repeatedly executing a generation calculation for generating a new individual that satisfies the provisional constraint condition by a genetic operation related to a genetic algorithm; and a condition change However, when the generation calculation unit executes the generation calculation, the step of changing the temporary contract power to a value close to the contract power, and the solution derivation unit, the temporary contract power is equal to the contract power And generating the charging schedule based on the individual generated by the generation calculation of the generation calculation unit.

  In addition, the present invention provides a provisional computer including a condition that a facility provided with a secondary battery prevents power received from the power system per unit time from exceeding a provisional contract power having a value higher than a predetermined contract power. An individual generation unit that generates an individual that satisfies a constraint condition, an evaluation value calculation unit that calculates an evaluation value for the individual using an evaluation function that derives an evaluation value that indicates higher evaluation as the electricity bill is smaller, and the evaluation value calculation unit A generation calculation unit that repeatedly executes generation calculation to generate a new individual that satisfies the temporary constraint condition by genetic operation according to a genetic algorithm by selecting the individual based on a probability based on the evaluation value calculated by A condition changing unit that changes the temporary contract power to a value close to the contract power when the generation calculation unit executes the generation calculation, after the temporary contract power becomes equal to the contract power , Based on an individual that has been generated by the generation calculation of the generation calculator is a program for functioning as a solution deriving unit for generating a charging schedule of the secondary battery.

  In addition, the present invention is a charge control system for controlling charging of a secondary battery in a facility including a secondary battery, wherein the power that the facility receives from the power system per unit time is higher than a predetermined contract power Using an individual generation unit that generates an individual that satisfies a temporary constraint condition including a condition that the provisional contract power is not exceeded, and an evaluation function that derives an evaluation value that indicates a higher evaluation as the electricity cost is smaller, An evaluation value calculation unit for calculating an evaluation value for the individual, and selecting the individual based on a probability based on the evaluation value calculated by the evaluation value calculation unit, and the temporary constraint condition by a genetic operation according to a genetic algorithm A generation calculation unit that repeatedly executes a generation calculation that generates a new individual that satisfies the condition, and when the generation calculation unit executes the generation calculation, the temporary contract power is a value close to the contract power A condition changing unit for changing, and a solution derivation unit for generating the charging schedule based on the individual generated by the generation calculation of the generation calculation unit after the provisional contract power becomes equal to the contract power. The apparatus includes a schedule generation device and a charger that charges the secondary battery according to a charging schedule generated by the solution derivation unit.

  According to the present invention, the solution search device and the schedule generation device can obtain an appropriate solution that satisfies the constraint conditions while easily generating an individual as an initial solution.

It is a schematic block diagram which shows the structure of the schedule production | generation apparatus which concerns on the 1st Embodiment of this invention. It is a figure which shows the example of the change method of a constraint condition. It is a flowchart which shows operation | movement of the schedule production | generation apparatus which concerns on the 1st Embodiment of this invention. It is a schematic block diagram which shows the structure of the charge control system which concerns on the 3rd Embodiment of this invention.

<< First Embodiment >>
Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.
The schedule generation device 100 (solution search device) according to the first embodiment satisfies a contract power condition in a facility including a plurality of EVs equipped with secondary batteries and a plurality of chargers that charge the EVs. It is a device that generates a charging schedule for a secondary battery to reduce the overall electricity bill. Here, the contract power is power defined by a contract with an electric power company as an upper limit value of power that can be supplied from the power system per unit time. The facility according to the first embodiment includes a plurality of chargers, and one charger cannot charge two or more EV secondary batteries at the same time.

FIG. 1 is a schematic block diagram showing the configuration of the schedule generation device 100 according to the first embodiment of the present invention.
The schedule generation device 100 includes a temporary constraint condition storage unit 101, an individual generation unit 102, a simulator unit 103, an evaluation value calculation unit 104, a generation calculation unit 105, a condition change unit 106, and a solution derivation unit 107.

  The temporary constraint condition storage unit 101 stores temporary constraint conditions that are looser than the constraint conditions to be satisfied by the charge / discharge schedule. In addition, the constraint conditions in this embodiment are the condition that the power supplied by the facility from the power system per unit time does not exceed the provisional contract power, and the chargers simultaneously charge a plurality of secondary batteries. The condition that it must not be. In this embodiment, provisional contract power is power that is larger than actual contract power.

  The individual generation unit 102 generates an individual satisfying the temporary constraint condition stored in the temporary constraint condition storage unit 101 as an initial solution. In this specification, “individual” means a solution candidate, that is, a candidate for a charging schedule of a secondary battery.

  The simulator unit 103 predetermines the time and time for running each EV and the time and time for using the equipment in the facility as the power consumption schedule of the facility, and the power consumption schedule and the individual generation unit 102 or generation calculation unit The power control of the facility is simulated using the individual generated by 105. The simulator unit 103 outputs power consumption and electricity cost per unit time as a result of the simulation.

  The evaluation value calculation unit 104 calculates an evaluation value for each individual using a simulation result by the simulator unit 103 and a predetermined evaluation function or a temporary evaluation function. In the present embodiment, the evaluation function is a function for deriving a higher evaluation value as an individual with a lower electricity bill. In the present embodiment, the provisional evaluation function is a function for deriving a higher evaluation value for an individual with a lower electricity cost and a lower peak power. Here, the peak power indicates the maximum value of power that the facility receives from the power system per unit time. The higher the evaluation value, the higher the degree of appropriateness and the evaluation.

  The generation calculation unit 105 selects an individual based on the probability based on the evaluation value calculated by the evaluation value calculation unit 104, and repeatedly executes generation calculation for generating a new individual by a genetic operation related to the genetic algorithm. The probability based on the evaluation value is a probability that an individual having a higher evaluation value is more likely to be selected. In addition, the generation calculation unit 105 generates an individual so as to satisfy the temporary constraint condition stored in the temporary constraint condition storage unit 101.

  The condition changing unit 106 changes the temporary constraint condition stored in the temporary constraint condition storage unit 101 to a condition close to the original constraint condition when the generation calculation unit 105 executes generation calculation. Specifically, the condition changing unit 106 decreases the temporary contract power set in the temporary constraint condition and changes it to a value close to the contract power. The condition changing unit 106 changes the constraint condition so that the number of generation calculation executions and the provisional contract power are monotonically non-increasing (decreasing monotonously in a broad sense).

  The solution deriving unit 107 derives the individual with the highest evaluation value from the individuals generated by the generation calculation of the generation calculating unit 105 after the temporary constraint condition becomes equal to the constraint condition, and satisfies the satisfaction based on the individual. Generate a discharge schedule.

Here, a method for changing the constraint condition by the condition changing unit 106 will be described.
FIG. 2 is a diagram illustrating an example of a constraint condition changing method.
For example, as shown in FIG. 2A, the condition changing unit 106 adjusts the difference between a certain amount of power (for example, the contract power and the initial provisional contract power each time the generation calculation unit 105 performs the generation calculation once. The provisional contract power may be reduced by the power obtained by dividing by the numerical value.

  In addition, as shown in FIG. 2B, the condition changing unit 106 does not change the value of the provisional contract power until the generation calculation is repeatedly executed to some extent, and after the generation calculation is repeatedly executed to some extent, The power may be reduced. In this case, the condition changing unit 106 may decrease the tentative power when the generation calculation is performed a predetermined number of times, for example, or when the peak power of each individual becomes equal to or lower than the predetermined power. Contract power may be reduced.

  Further, as shown in FIG. 2C, the condition changing unit 106 may decrease the provisional contract power every time generation calculation is repeatedly performed to some extent. In this case, the condition changing unit 106 may decrease the tentative power when the generation calculation is performed a predetermined number of times, for example, or when the peak power of each individual becomes equal to or lower than the predetermined power. Contract power may be reduced.

  In addition, the condition change unit 106 may use the change method according to the situation. When the condition changing unit 106 monitors the peak power of each individual and determines whether or not to decrease the provisional contract power, the constraint condition can be tightened according to the degree of convergence of each individual. The optimal solution search can be performed.

Next, the operation of the schedule generation device 100 according to the first embodiment of the present invention will be described.
FIG. 3 is a flowchart showing the operation of the schedule generation device 100 according to the first embodiment of the present invention.
First, the individual generation unit 102 of the schedule generation device 100 generates N individuals that satisfy the temporary constraint condition stored in the temporary constraint condition storage unit 101 (step S1). The individual generation unit 102 may generate a solid based on a random number, or may generate an individual by a user's manual input or the like.

  Next, the simulator unit 103 simulates the power control of the facility for each individual set by the individual generation unit 102, and calculates the power and the electricity bill supplied from the power system every unit time (step S2). ). Next, the evaluation value calculation unit 104 determines whether or not the current temporary constraint condition is equal to the actual constraint condition (step S3). That is, the evaluation value calculation unit 104 determines whether the provisional contract power and the actual contract power are equal.

  When the evaluation value calculation unit 104 determines that the temporary contract power and the actual contract power are different (step S3: NO), the evaluation value calculation unit 104 evaluates each individual using the simulation result by the simulator unit 103 and the above-described temporary evaluation function. A value is calculated (step S4). Next, the condition changing unit 106 rewrites the temporary constraint condition stored in the temporary constraint condition storage unit 101 to a condition close to the constraint condition (step S5).

  Next, the generation calculation unit 105 performs a genetic operation based on a genetic algorithm for each individual. That is, the generation calculation unit 105 selects, crosses, or mutates so that an individual with a high evaluation value remains among individuals of a generation generated by the individual generation unit 102 or generated by the generation calculation unit 105. Perform the generation calculation to generate the next generation individuals. The generation calculation unit 105 performs generation calculation by repeatedly executing the operations in steps S6 to S11 described below.

  First, the generation calculation unit 105 randomly determines whether to perform selection, crossover, or mutation (step S6). In general, in the genetic algorithm, the probability of determining which process is performed is set in the order of the probability of performing a crossover operation ≧ the probability of performing a selection operation ≧ the probability of performing a mutation operation.

  When the generation calculation unit 105 decides to perform a crossover operation (step S6: crossover), the generation calculation unit 105 selects two of the plurality of individuals according to the probability based on the weight corresponding to the evaluation value calculated by the evaluation value calculation unit 104. An individual is selected (step S7). That is, an individual with a higher evaluation value has a greater weight and is easily selected by the generation calculation unit 105.

  Next, the generation calculation unit 105 replaces a part of the two selected individuals to generate a new individual (step S8). As a crossover method, it is preferable that the generation calculation unit 105 is two individuals, and the charge schedule is switched for each charger. As a result, by performing crossover in units of chargers, new individuals can be obtained within a range that does not violate the condition that each of the chargers must not charge a plurality of secondary batteries at the same time, which is one of the temporary constraints. be able to.

  In addition, when the generation calculation unit 105 determines to perform a mutation operation in step S6 (step S6: mutation), the weight according to the evaluation value calculated by the evaluation value calculation unit 104 from a plurality of individuals. One individual is selected according to the probability based on (step S9).

  Next, the generation calculation unit 105 newly generates a pattern of adjustment values by rewriting a part of the selected individual (step S10). As a method of mutation, in a selected individual, a part that a certain charger charges a secondary battery is randomly selected, and the selected part and a part where the charger does not charge any secondary battery; Is preferably replaced. Thereby, a new individual can be obtained as long as it does not violate the condition that each of the chargers, which is one of temporary constraint conditions, must not charge a plurality of secondary batteries at the same time.

  In addition, when the generation calculation unit 105 determines to perform a selection operation in step S6 (step S6: selection), the generation calculation unit 105 is based on a weight corresponding to the evaluation value calculated by the evaluation value calculation unit 104 from among a plurality of individuals. One individual is extracted according to the probability (step S11).

When the generation calculation unit 105 extracts an individual through the processing of steps S6 to S11 described above, the generation calculation unit 105 determines whether the temporary constraint condition stored in the temporary constraint condition storage unit 101 for the individual is satisfied (step S12). Then, the generation calculation unit 105 repeatedly executes the processes in steps S6 to S11 until N individuals that satisfy the temporary constraint condition are extracted.
On the other hand, when the generation calculation unit 105 extracts N individuals that satisfy the provisional constraint condition, the generation calculation unit 105 returns to step S2 and performs power control simulation for each individual.

  When the temporary constraint condition and the constraint condition become equal in step S3 by repeatedly executing the above processing (step S3: YES), the evaluation value calculation unit 104 uses the simulation result by the simulator unit 103 and the evaluation function described above. Then, an evaluation value is calculated for each individual (step S13). Then, the solution deriving unit 107 determines whether or not a predetermined end condition is satisfied (step S14). As an example of the end condition, for example, when the generation calculation is performed a predetermined number of times after the temporary constraint condition and the constraint condition are equal, or the difference between the maximum value and the minimum value of the evaluation value calculated by the evaluation value calculation unit 104 Is less than a predetermined value.

  If the solution deriving unit 107 determines that the end condition is not satisfied (step S14: NO), the solution deriving unit 107 performs generation calculation according to steps S6 to S12. On the other hand, when determining that the termination condition is satisfied (step S14: YES), the solution deriving unit 107 identifies the individual having the highest evaluation value among the individuals generated by the generation calculation unit 105, and performs charging based on the individual. A schedule is generated (step S15).

  As described above, according to the schedule generation device 100 according to the first embodiment of the present invention, the individual generation unit 102 generates, as an initial solution, an individual that satisfies a temporary constraint condition that is a relatively looser condition than the constraint condition. . Thereby, the schedule generation device 100 can easily generate the initial solution even when the constraint condition is severe. In addition, according to the schedule generation device 100 according to the first exemplary embodiment of the present invention, the solution derivation unit 107 identifies an individual to be a solution after the temporary constraint condition and the constraint condition become equal. As a result, the schedule generation device 100 can obtain an appropriate solution that satisfies the constraint conditions.

  Further, according to the schedule generation device 100 according to the first exemplary embodiment of the present invention, the evaluation value calculation unit 104 calculates an evaluation value indicating a higher evaluation as the peak power is smaller until the temporary constraint condition becomes equal to the constraint condition. An evaluation value is calculated using the derived temporary evaluation function. That is, the evaluation value calculation unit 104 calculates an evaluation value using a temporary evaluation function that derives an evaluation value indicating higher evaluation as an individual is closer to a value satisfying the constraint condition until the temporary constraint condition becomes equal to the constraint condition. Thereby, the individual obtained by the generation calculation can be brought close to the individual satisfying the constraint every time the generation calculation is performed.

  Further, according to the schedule generation device 100 according to the first embodiment of the present invention, the generation calculation unit 105 executes a genetic operation within a range that does not violate at least one of the temporary constraint conditions. Thereby, compared with the case where genetic operation is performed unconditionally, the number of genetic operations by the generation calculation unit 105 can be relatively reduced, and the overall calculation time can be shortened.

<< Second Embodiment >>
Next, a second embodiment of the present invention will be described.
In general, the nighttime electricity bill is often set at a lower cost than the daytime electricity bill. Therefore, there is a high possibility that the electricity bill can be reduced at a low cost by charging the secondary battery at night. In the schedule generation device 100 according to the second embodiment, when the portion of the individual whose evaluation value is likely to fluctuate is known as an empirical rule, the probability that the portion is an operation target is increased. By performing the operation, an appropriate charging schedule is obtained in a short calculation time.

  Specifically, the generation calculation unit 105 according to the second embodiment selects a non-charged part in a time zone with a low electricity bill when performing a mutation that changes a non-charged part to a charged part for an individual. Mutation operations are performed based on the probability that the possibility is high.

  As described above, according to the second embodiment of the present invention, the probability that the part to be subjected to the mutation operation in the generation calculation unit 105 is selected varies depending on the time zone. As a result, the generation calculation unit 105 can increase the probability of generating an individual with a high evaluation value based on the evaluation function of reducing the electricity bill, and the overall calculation time can be shortened.

<< Third Embodiment >>
Next, a third embodiment of the present invention will be described.
FIG. 4 is a schematic block diagram showing the configuration of the charging control system 10 according to the third embodiment of the present invention.
The charge / discharge control system includes a schedule generation device 100 according to the second embodiment and a plurality of chargers 200, and the schedule generation device 100 and each charger 200 are connected by wire or wirelessly. Each charger 200 includes a charge control unit 201 and a usage information acquisition unit 202.

  The charging control unit 201 acquires the charging schedule generated by the solution derivation unit 107 of the schedule generation device 100, and charges the EV secondary battery according to the charging schedule.

  The usage information acquisition unit 202 acquires parameters used by the schedule generation device 100 to generate a schedule from the user. Examples of parameters include contract power, provisional contract power, and power consumption per unit time of equipment. In addition, the usage information acquisition unit 202 acquires the time when the secondary battery is connected and the charging rate of the secondary battery, and based on this information, calculates the time zone where the EV is used and the power consumption of the EV. The information may be estimated and used as a parameter for simulation by the simulator unit 103.

  Thus, according to the charge / discharge control system according to the third embodiment, the secondary battery can be charged according to the charge schedule generated by the schedule generation device 100 according to the second embodiment. Further, according to the charge / discharge control system according to the third embodiment, information for generating a charging schedule can be input to the schedule generating device 100.

  In the third embodiment of the present invention, the case where the usage information acquisition unit 202 is provided in the charger 200 has been described. However, the present invention is not limited to this. For example, the schedule generation device 100 includes the usage information acquisition unit 202. Also good.

  In the third embodiment of the present invention, the case where the schedule generation device 100 and the charger 200 are separately provided has been described. However, the present invention is not limited to this, and one of the plurality of chargers 200 is included in the schedule generation device 100. It may have a function.

  Although several embodiments of the present invention have been described in detail with reference to the drawings, the specific configuration is not limited to that described above, and various designs can be made without departing from the scope of the present invention. It is possible to make changes.

  For example, in the above-described embodiment, the case where the solution search apparatus according to the present invention is implemented in the schedule generation apparatus 100 has been described. However, the present invention is not limited to this, and the solution search apparatus is implemented in another apparatus using a genetic algorithm. Also good. Specifically, the solution search device according to the present invention includes a device for searching an appropriate route in route search, a device for formulating a factory production plan, a device for formulating a structure of a structure that minimizes a member cross-sectional area, and the like. May be implemented.

  Moreover, although embodiment mentioned above demonstrated the case where an installation was provided with two or more chargers 200, it is not restricted to this, Even if the schedule production | generation apparatus 100 produces | generates a charging schedule about the installation provided with only one charger 200, it is. good.

  Moreover, although embodiment mentioned above demonstrated the case where the charger 200 charges the secondary battery mounted in EV, it is not restricted to this, The charger 200 charges other secondary batteries, such as a non-stop power supply device. It may be what performs.

  Moreover, although embodiment mentioned above demonstrated the case where the schedule production | generation apparatus 100 produced | generated the charging schedule of a secondary battery, it is not restricted to this, In addition to this, the schedule production | generation apparatus 100 discharges a secondary battery. A discharge schedule to be controlled may be generated.

  The above-described schedule generation device 100 has a computer system inside. The operation of each processing unit described above is stored in a computer-readable recording medium in the form of a program, and the above processing is performed by the computer reading and executing this program. Here, the computer-readable recording medium means a magnetic disk, a magneto-optical disk, a CD-ROM, a DVD-ROM, a semiconductor memory, or the like. Alternatively, the computer program may be distributed to the computer via a communication line, and the computer that has received the distribution may execute the program.

  The program may be for realizing a part of the functions described above. Furthermore, what can implement | achieve the function mentioned above in combination with the program already recorded on the computer system, and what is called a difference file (difference program) may be sufficient.

  DESCRIPTION OF SYMBOLS 10 ... Charge control system 100 ... Schedule production | generation apparatus 101 ... Temporary constraint condition memory | storage part 102 ... Individual production | generation part 103 ... Simulator part 104 ... Evaluation value calculation part 105 ... Generation calculation part 106 ... Condition change part 107 ... Solution derivation part 200 ... Charging 201 ... Charge control unit 202 ... Use information acquisition unit

Claims (13)

A solution search device for searching for a solution that satisfies a constraint condition,
An individual generation unit for generating an individual satisfying a temporary constraint condition that is a condition looser than the constraint condition;
An evaluation value calculation unit for calculating an evaluation value for the individual using a predetermined evaluation function;
The individual is selected based on the probability based on the evaluation value calculated by the evaluation value calculation unit, and generation generation for generating a new individual that satisfies the temporary constraint condition through a genetic operation related to a genetic algorithm is repeatedly executed. The generation calculator,
A condition changing unit that changes the temporary constraint condition to a condition close to the constraint condition when the generation calculation unit executes the generation calculation;
A solution search apparatus comprising: a solution derivation unit that derives a solution from an individual generated by the generation calculation of the generation calculation unit after the temporary constraint condition becomes equal to the constraint condition. The evaluation value calculation unit uses a temporary evaluation function for deriving an evaluation value indicating a higher evaluation as the individual is closer to a value satisfying the constraint condition until the temporary constraint condition is equal to the constraint condition. An evaluation value is calculated for the individual, and after the temporary constraint condition is equal to the constraint condition, an evaluation value is calculated for the individual using the evaluation function,
The solution derivation unit derives a solution from an individual generated by the generation calculation of the generation calculation unit based on the evaluation value calculated by the evaluation value calculation unit using the evaluation function. The solution search apparatus according to 1. The solution search device according to claim 1, wherein the generation calculation unit executes the genetic operation within a range that does not violate at least one of the temporary constraint conditions. The generation calculation unit, when performing a mutation operation in the genetic operation, based on a predetermined probability that the portion of the individual whose evaluation value is likely to vary is likely to be the target of the genetic operation The solution search device according to any one of claims 1 to 3, wherein the genetic operation is performed. A solution search method using a solution search device for searching for a solution that satisfies a constraint condition,
An individual generating unit generating an individual satisfying a temporary constraint condition that is a condition looser than the constraint condition;
An evaluation value calculating unit calculating an evaluation value for the individual using a predetermined evaluation function;
A generation in which a generation calculation unit selects the individual based on the probability based on the evaluation value calculated by the evaluation value calculation unit, and generates a new individual that satisfies the temporary constraint condition through a genetic operation related to a genetic algorithm A step of repeatedly performing the calculation;
A condition changing unit, when the generation calculating unit executes the generation calculation, changing the temporary constraint condition to a condition close to the constraint condition;
A solution derivation unit comprising: deriving a solution from an individual generated by the generation calculation of the generation calculation unit after the temporary constraint condition is equal to the constraint condition. Computer
An individual generation unit that generates an individual that satisfies a temporary constraint condition that is looser than a predetermined constraint condition;
An evaluation value calculation unit that calculates an evaluation value for the individual using a predetermined evaluation function,
The individual is selected based on the probability based on the evaluation value calculated by the evaluation value calculation unit, and generation generation for generating a new individual that satisfies the temporary constraint condition through a genetic operation related to a genetic algorithm is repeatedly executed. Generation calculator,
A condition changing unit that changes the temporary constraint condition to a condition close to the constraint condition when the generation calculation unit executes the generation calculation;
A program for functioning as a solution derivation unit for deriving a solution from an individual generated by the generation calculation of the generation calculation unit after the temporary constraint condition becomes equal to the constraint condition. A schedule generation device that generates a charging schedule for the secondary battery in a facility including the secondary battery,
An individual generating unit that generates an individual that satisfies a provisional constraint condition including a condition that power received by the facility from the power system per unit time does not exceed provisional contract power that is higher than predetermined contract power; and ,
Using an evaluation function for deriving an evaluation value indicating a higher evaluation as the electricity bill is smaller, an evaluation value calculation unit that calculates an evaluation value for the individual,
The individual is selected based on the probability based on the evaluation value calculated by the evaluation value calculation unit, and generation generation for generating a new individual that satisfies the temporary constraint condition through a genetic operation related to a genetic algorithm is repeatedly executed. The generation calculator,
A condition changing unit for changing the provisional contract power to a value close to the contract power when the generation calculation unit executes the generation calculation;
A schedule derivation unit comprising: a solution derivation unit configured to generate the charging schedule based on an individual generated by the generation calculation of the generation calculation unit after the provisional contract power becomes equal to the contract power. apparatus. The evaluation value calculation unit derives an evaluation value indicating a higher evaluation value as the maximum value of the power supplied from the power system to the facility per unit time is smaller until the temporary contract power becomes equal to the contract power. A function is used to calculate an evaluation value for the individual, and after the provisional contract power is equal to the contract power, the evaluation function is used to calculate an evaluation value for the individual,
The solution derivation unit derives a solution from an individual generated by the generation calculation of the generation calculation unit based on the evaluation value calculated by the evaluation value calculation unit using the evaluation function. 8. The schedule generation device according to 7. The facility includes a plurality of chargers for charging the secondary battery and the secondary battery,
The temporary constraint condition includes a condition that each of the chargers must not charge a plurality of secondary batteries at the same time,
The schedule generation device according to claim 7 or 8, wherein the generation calculation unit performs an operation in units of the charger when performing a crossover operation or a mutation operation in the genetic operation. The generation calculation unit, when performing a mutation operation in the genetic operation, the genetic calculation based on a predetermined probability that a time zone in which the electricity bill is low among the individuals is a target of the genetic operation is high. The schedule generation device according to any one of claims 7 to 9, wherein a manual operation is performed. A schedule generation method using a schedule generation device that generates a charging schedule of the secondary battery in a facility including the secondary battery,
The individual generation unit generates an individual that satisfies a provisional constraint condition including a condition that the power supplied from the power system to the facility per unit time does not exceed a provisional contract power with a value higher than a predetermined contract power. Steps,
The evaluation value calculation unit calculates an evaluation value for the individual using an evaluation function for deriving an evaluation value indicating higher evaluation as the electricity cost is smaller;
A generation in which a generation calculation unit selects the individual based on the probability based on the evaluation value calculated by the evaluation value calculation unit, and generates a new individual that satisfies the temporary constraint condition through a genetic operation related to a genetic algorithm A step of repeatedly performing the calculation;
A condition changing unit, when the generation calculation unit executes the generation calculation, changing the temporary contract power to a value close to the contract power;
A solution derivation unit comprising: generating the charging schedule based on the individual generated by the generation calculation of the generation calculation unit after the provisional contract power becomes equal to the contract power. Schedule generation method. Computer
An individual that generates an individual that satisfies the provisional constraint condition including the condition that the equipment provided with the secondary battery does not exceed the provisional contract power that is higher than the predetermined contract power by the power supplied from the power system per unit time. Generator,
An evaluation value calculation unit for calculating an evaluation value for the individual using an evaluation function for deriving an evaluation value indicating a higher evaluation as the electricity cost is smaller,
A generation calculation for generating a new individual satisfying the temporary constraint condition is repeatedly executed by selecting the individual based on a probability based on the evaluation value calculated by the evaluation value calculation unit and performing a genetic operation related to a genetic algorithm. Generation calculator,
A condition changing unit that changes the provisional contract power to a value close to the contract power when the generation calculation unit executes the generation calculation;
A program for functioning as a solution derivation unit that generates a charging schedule for the secondary battery based on an individual generated by the generation calculation of the generation calculation unit after the provisional contract power becomes equal to the contract power . A charge control system for controlling charging of the secondary battery in a facility including the secondary battery,
An individual generating unit that generates an individual that satisfies a provisional constraint condition including a condition that power received by the facility from the power system per unit time does not exceed provisional contract power that is higher than predetermined contract power; and ,
Using an evaluation function for deriving an evaluation value indicating a higher evaluation as the electricity bill is smaller, an evaluation value calculation unit that calculates an evaluation value for the individual,
The individual is selected based on the probability based on the evaluation value calculated by the evaluation value calculation unit, and generation generation for generating a new individual that satisfies the temporary constraint condition through a genetic operation related to a genetic algorithm is repeatedly executed. The generation calculator,
A condition changing unit for changing the provisional contract power to a value close to the contract power when the generation calculation unit executes the generation calculation;
A schedule generation device comprising: a solution derivation unit that generates the charging schedule based on an individual generated by the generation calculation of the generation calculation unit after the provisional contract power becomes equal to the contract power;
A charging control system comprising: a charger that charges the secondary battery according to a charging schedule generated by the solution deriving unit.

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