JP2013196322A - Control device and control method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a control device and a control method which are capable of suppressing increase of calculation quantity and enhancing calculation accuracy of an optimum solution.SOLUTION: A HEMS 200 includes: a calculation unit 240 that utilizes, as an element, an operation of a PV unit 130, a storage battery unit 140, a fuel cell unit 150, or a hot water storage unit 160, and calculates, every unit time, an optimum solution including at least one of a purchase charge of electric power supplied from a system and a sales charge of electric power provided to the system; and a creation unit 230 that creates a correlation between a calculation time and a calculation accuracy of the optimum solution, in each of unit times with different length.

Description

  The present invention relates to a control device and a control method for controlling a distributed power source, a power storage device, or a heat storage device.

  In recent years, methods for optimizing the operation of a distributed power source, a power storage device, and a heat storage device have been proposed. A distributed power source is a device that generates electric power using natural energy such as sunlight, wind power, and geothermal heat, such as a solar battery. Or a distributed power supply is an apparatus which produces | generates electric power using fuel gas like fuel cells, such as SOFC (Solid Oxide Fuel Cell). The power storage device is a device that stores electric power, such as a secondary battery. The heat storage device is a device that stores electric power by converting electric power into heat, such as a water heater.

  For example, by controlling charging / discharging of a power storage device, a technique for optimizing the amount of power supplied from the grid (amount of power purchased) and minimizing the purchase price of power has been proposed (for example, Patent Document 1, 2). Or the technique of determining the driving | running pattern of a fuel cell for every unit time obtained by dividing | segmenting a predetermined period based on the prediction result of the energy load in a predetermined period is proposed (for example, patent document 3).

  By the way, in order to obtain a solution such as minimization of a power purchase fee, a method for calculating an optimum solution for each unit time by searching for a combination of a plurality of elements that affect the solution is known. Such methods are called greedy methods, greedy methods, greedy methods, and the like.

Japanese Patent Laid-Open No. 2002-247761 JP 2007-020260 A JP 2007-220665 A

  As described above, in the method of calculating an optimal solution such as minimization of the power purchase fee (hereinafter referred to as “greedy method”), the optimal solution can be calculated every unit time.

  However, if the unit time obtained by dividing a predetermined period (for example, 24 hours) is long, the number of elements that affect the solution increases, so the amount of calculation for calculating the optimum solution for the entire predetermined period increases. To do. On the other hand, when the unit time is short, the calculation accuracy of the optimum solution for the entire predetermined period is lowered.

  Therefore, the present invention has been made to solve the above-described problems, and provides a control device and a control method that can achieve both suppression of increase in the amount of computation and computation accuracy of an optimal solution. With the goal.

  The control device according to the first feature is a device for controlling a distributed power source, a power storage device, or a heat storage device. The control device has the operation of the distributed power source, the power storage device or the heat storage device as an element, and at least one of a purchase fee of power supplied from the grid and a sale fee of power provided to the grid, By searching for a combination of elements, a calculation unit that calculates an optimal solution for each unit time obtained by dividing a predetermined period, and for each unit time having a different time length, the calculation time of the optimal solution and the optimal A generating unit that generates a correspondence relationship with the calculation accuracy of the solution.

  In the first feature, the generation unit generates the correspondence relationship for each day of the week, weather, or season.

  In the first feature, the control device includes: a specifying unit that specifies a time length of an optimal unit time from the correspondence generated for each unit time having a different time length; and a unit used for the calculation of the optimal solution As a time, a selection unit is provided for selecting a unit time having the optimum unit time length.

  In the first feature, the selection unit has a time length shorter than a time length of the optimal unit time as a unit time used for the calculation of the optimal solution when the processing load of the calculation unit is equal to or greater than a threshold. Select the unit time you have.

  The control method according to the second feature is a method for controlling a distributed power source, a power storage device, or a heat storage device. The control method is provided to the system for purchasing power supplied from the grid and for each unit time obtained by dividing a predetermined period, using the operation of the distributed power source, the power storage device or the heat storage device as an element. And generating a correspondence between the calculation time of the optimal solution and the calculation accuracy of the optimal solution for each unit time having a different time length, using at least one of the power sales fees of the electric power as a solution Steps.

  ADVANTAGE OF THE INVENTION According to this invention, the control apparatus and control method which can aim at the coexistence of the increase suppression of calculation amount and the calculation accuracy of the optimal solution can be provided.

FIG. 1 is a diagram illustrating an energy management system 100 according to the first embodiment. FIG. 2 is a diagram illustrating the customer 10 according to the first embodiment. FIG. 3 is a diagram illustrating the HEMS 200 according to the first embodiment. FIG. 4 is a diagram for explaining the change of the time length of the unit time according to the first embodiment. FIG. 5 is a diagram for explaining a correspondence relationship between calculation time and calculation accuracy according to the first embodiment. FIG. 6 is a diagram for explaining a correspondence relationship between calculation time and calculation accuracy according to the first embodiment. FIG. 7 is a diagram illustrating an example of a correspondence relationship between calculation time and calculation accuracy according to the first embodiment. FIG. 8 is a diagram for explaining an objective function according to the first embodiment. FIG. 9 is a diagram for explaining the element combination search method according to the first embodiment. FIG. 10 is a flowchart showing the control method according to the first embodiment. FIG. 11 is a flowchart showing the control method according to the first embodiment.

  Hereinafter, a control device according to an embodiment of the present invention will be described with reference to the drawings. In the following description of the drawings, the same or similar parts are denoted by the same or similar reference numerals.

  However, it should be noted that the drawings are schematic and ratios of dimensions and the like are different from actual ones. Therefore, specific dimensions and the like should be determined in consideration of the following description. Moreover, it is a matter of course that portions having different dimensional relationships and ratios are included between the drawings.

[Outline of Embodiment]
The control apparatus which concerns on embodiment is an apparatus for controlling a distributed power supply, an electrical storage apparatus, or a thermal storage apparatus. The control device has the operation of the distributed power source, the power storage device or the heat storage device as an element, and at least one of a purchase fee of power supplied from the grid and a sale fee of power provided to the grid, By searching for a combination of elements, a calculation unit that calculates an optimal solution for each unit time obtained by dividing a predetermined period, and for each unit time having a different time length, the calculation time of the optimal solution and the optimal A generating unit that generates a correspondence relationship with the calculation accuracy of the solution.

  In the embodiment, the generation unit generates a correspondence relationship between the calculation time of the optimal solution and the calculation accuracy of the optimal solution for each unit time having a different time length. Therefore, it is possible to select the time length of the unit time for calculating the optimum solution while referring to the correspondence relationship. As a result, it is possible to achieve both suppression of increase in the amount of calculation and calculation accuracy of the optimal solution.

[First Embodiment]
(Energy management system)
Hereinafter, the energy management system according to the first embodiment will be described. FIG. 1 is a diagram illustrating an energy management system 100 according to the first embodiment.

  As shown in FIG. 1, the energy management system 100 includes a customer 10, a CEMS 20, a substation 30, a smart server 40, and a power plant 50. The customer 10, the CEMS 20, the substation 30 and the smart server 40 are connected by a network 60.

  The customer 10 has at least one of a distributed power source, a power storage device, and a heat storage device. A distributed power source is a device that generates electric power using natural energy such as sunlight, wind power, and geothermal heat, such as a solar battery. Or a distributed power supply is an apparatus which produces | generates electric power using fuel gas like a fuel cell, for example. The power storage device is a device that stores electric power, such as a secondary battery. The heat storage device is a device that stores electric power by converting electric power into heat, such as a water heater.

  For example, the customer 10 may be a single-family house, an apartment house such as a condominium, a commercial facility such as a building, or a factory.

  In the first embodiment, a customer group 10 </ b> A and a customer group 10 </ b> B are configured by a plurality of consumers 10. The consumer group 10A and the consumer group 10B are classified by, for example, a geographical area.

  The CEMS 20 controls interconnection between the plurality of consumers 10 and the power system. The CEMS 20 is sometimes referred to as a CEMS (Cluster Energy Management System) in order to manage a plurality of consumers 10. Specifically, the CEMS 20 disconnects between the plurality of consumers 10 and the power system at the time of a power failure or the like. On the other hand, the CEMS 20 interconnects the plurality of consumers 10 and the power system when power is restored.

  In the first embodiment, a CEMS 20A and a CEMS 20B are provided. For example, the CEMS 20A controls interconnection between the customer 10 included in the customer group 10A and the power system. For example, the CEMS 20B controls interconnection between the customer 10 included in the customer group 10B and the power system.

  The substation 30 supplies electric power to the plurality of consumers 10 via the distribution line 31. Specifically, the substation 30 steps down the voltage supplied from the power plant 50.

  In the first embodiment, a substation 30A and a substation 30B are provided. For example, the substation 30A supplies power to the consumers 10 included in the consumer group 10A via the distribution line 31A. For example, the substation 30B supplies power to the consumers 10 included in the consumer group 10B via the distribution line 31B.

  The smart server 40 manages a plurality of CEMSs 20 (here, CEMS 20A and CEMS 20B). The smart server 40 also manages a plurality of substations 30 (here, the substation 30A and the substation 30B). In other words, the smart server 40 comprehensively manages the customers 10 included in the customer group 10A and the customer group 10B. For example, the smart server 40 has a function of balancing the power to be supplied to the consumer group 10A and the power to be supplied to the consumer group 10B.

  The power plant 50 generates power using thermal power, wind power, hydraulic power, nuclear power, and the like. The power plant 50 supplies power to the plurality of substations 30 (here, the substation 30A and the substation 30B) via the power transmission line 51.

  The network 60 is connected to each device via a signal line. The network 60 is, for example, the Internet, a wide area network, a narrow area network, a mobile phone network, or the like.

(Customer)
Below, the consumer which concerns on 1st Embodiment is demonstrated. FIG. 2 is a diagram illustrating details of the customer 10 according to the first embodiment.

  As shown in FIG. 2, the customer 10 includes a distribution board 110, a load 120, a PV unit 130, a storage battery unit 140, a fuel cell unit 150, a hot water storage unit 160, and a HEMS 200.

  Distribution board 110 is connected to distribution line 31 (system). Distribution board 110 is connected to load 120, PV unit 130, storage battery unit 140, and fuel cell unit 150 via a power line.

  The distribution board 110 may have a measurement unit that measures electric power supplied from the distribution line 31 (system). The measurement unit may measure the power consumption of the load 120.

  The load 120 is a device that consumes power supplied via the power line. For example, the load 120 includes devices such as a refrigerator, lighting, an air conditioner, and a television. The load 120 may be a single device or may include a plurality of devices.

  The PV unit 130 includes a PV 131 and a PCS 132. The PV 131 is an example of a distributed power source, and is a device that generates power in response to reception of sunlight. The PV 131 outputs the generated DC power. The amount of power generated by the PV 131 changes according to the amount of solar radiation applied to the PV 131. The PCS 132 is a device (Power Conditioning System) that converts DC power output from the PV 131 into AC power. The PCS 132 outputs AC power to the distribution board 110 via the power line.

  In the first embodiment, the PV unit 130 may have a pyranometer that measures the amount of solar radiation irradiated on the PV 131.

  The PV unit 130 is controlled by an MPPT (Maximum Power Point Tracking) method. Specifically, the PV unit 130 optimizes the operating point (a point determined by the operating point voltage value and the power value, or a point determined by the operating point voltage value and the current value) of the PV 131.

  The storage battery unit 140 includes a storage battery 141 and a PCS 142. The storage battery 141 is a device that stores electric power. The PCS 142 is a device (Power Conditioning System) that converts DC power output from the storage battery 141 into AC power.

  The fuel cell unit 150 includes a fuel cell 151 and a PCS 152. The fuel cell 151 is an example of a distributed power source, and is a device that generates electric power using fuel gas. The PCS 152 is a device (Power Conditioning System) that converts DC power output from the fuel cell 151 into AC power.

  The fuel cell unit 150 operates by load following control. Specifically, the fuel cell unit 150 controls the fuel cell 151 so that the power output from the fuel cell 151 follows the power consumption of the load 120.

  The hot water storage unit 160 is an example of a heat storage device that converts electric power into heat and accumulates heat. Specifically, the hot water storage unit 160 has a hot water storage tank, and warms water supplied from the hot water storage tank by exhaust heat generated by the operation (power generation) of the fuel cell 151. Specifically, the hot water storage unit 160 warms the water supplied from the hot water storage tank and returns the warmed hot water to the hot water storage tank.

  The HEMS 200 is a control device for controlling a distributed power source, a power storage device, or a heat storage device.

  In the first embodiment, the HEMS 200 is connected to the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160 via signal lines, and the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage. The unit 160 is controlled. Further, the HEMS 200 may control the power consumption of the load 120 by controlling the operation mode of the load 120.

  The HEMS 200 is connected to various servers via the network 60. Various servers store, for example, information (hereinafter, energy fee information) such as a unit price of power supplied from the grid, a unit price of power sold from the grid, and a unit price of fuel gas.

  Or various servers store the information (henceforth energy consumption prediction information) for predicting the power consumption of the load 120, for example. The energy consumption prediction information may be generated based on, for example, the past power consumption actual value of the load 120. Alternatively, the energy consumption prediction information may be a model of power consumption of the load 120.

  Or various servers store the information (henceforth PV power generation amount prediction information) for predicting the power generation amount of PV131, for example. The PV power generation prediction information may be a predicted value of the amount of solar radiation irradiated on the PV 131. Alternatively, the PV power generation prediction information may be weather forecast, season, sunshine time, and the like.

  Specifically, as illustrated in FIG. 3, the HEMS 200 includes a reception unit 210, a transmission unit 220, a generation unit 230, a calculation unit 240, and a control unit 250.

  The receiving unit 210 receives various signals from a device connected via a signal line. For example, the receiving unit 210 receives information indicating the power generation amount of the PV 131 from the PV unit 130. The receiving unit 210 receives information indicating the storage amount of the storage battery 141 from the storage battery unit 140. The receiving unit 210 receives information indicating the power generation amount of the fuel cell 151 from the fuel cell unit 150. The receiving unit 210 receives information indicating the amount of hot water stored in the hot water storage unit 160 from the hot water storage unit 160.

  In the first embodiment, the reception unit 210 may receive energy charge information, energy consumption prediction information, and PV power generation amount prediction information from various servers via the network 60. However, the energy fee information, the energy consumption prediction information, and the PV power generation amount prediction information may be stored in the HEMS 200 in advance.

  The transmission unit 220 transmits various signals to a device connected via a signal line. For example, the transmission part 220 transmits the signal for controlling the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160 to each apparatus.

  The generation unit 230 generates a correspondence relationship (for example, a table) between the calculation time of the optimal solution and the calculation accuracy of the optimal solution for each unit time having a different time length. The unit time is a time for which an optimum solution should be calculated by the calculation unit 240 described later. The unit time is a time obtained by dividing a predetermined period (for example, 24 hours, one week, one month, three months (seasonal period), etc.).

  Here, the concept of changing the time length of the unit time will be described with reference to FIG. In FIG. 4, the amount of power generated by the PV unit 130 (PV [Wh] in FIG. 4), the power consumption of the load 120 (CONSUME [Wh] in FIG. 4), and the unit price of power purchased from the system (in FIG. 4, BUY [Cent]), and the sale price of power provided to the grid (SELL [Cent] in FIG. 4) are illustrated as transitions in a predetermined period (3 days in FIG. 4).

  In the first embodiment, the generation unit 230 generates in advance a correspondence relationship (for example, a table) between the calculation time of the optimal solution and the calculation accuracy of the optimal solution for each time length of a unit time obtained by dividing a predetermined period. To do.

  Here, as shown in FIG. 5, for example, as shown in FIG. 5, the longer the unit time, the longer the optimal solution calculation time, and the optimal solution calculation accuracy (power Purchase price) is high.

  However, as shown in FIG. 5, the optimal solution (power purchase fee) corresponding to the second unit time (for example, 8 hours) longer than the first unit time (for example, 6 hours) is the first unit. There is a case that is worse than the optimal solution (power purchase fee) corresponding to time. In such a case, there is no merit of calculating the optimum solution in the second unit time. Therefore, as shown in FIG. 6, the second unit time is preferably excluded from the correspondence (for example, a table) between the calculation time of the optimal solution and the calculation accuracy of the optimal solution.

  Finally, the generation unit 230 generates a correspondence relationship (for example, a table) illustrated in FIG. In the correspondence relationship (for example, table) shown in FIG. 7, the optimization level, the time length, the calculation time, and the optimization accuracy are associated with each other.

  The optimization level is a value indicating the degree of calculation accuracy of the optimal solution. Here, the calculation accuracy of the optimum solution is higher as the value of the optimization level is larger. The time length is a time length of a unit time. The calculation time is the time required for calculating the optimal solution as a whole for a predetermined period when the optimal solution is calculated every corresponding unit time. The optimization accuracy is a value indicating the calculation accuracy of the optimal solution. In the example shown in FIG. 7, the optimization accuracy at the optimization level n (1 ≦ n ≦ 7) indicates the ratio (%) of the optimal solution at the optimization level n to the optimal solution with the highest calculation accuracy.

  Here, the optimization accuracy is used as the calculation accuracy of the optimal solution, but the calculation accuracy of the optimal solution may be the value of the optimal solution (for example, a power purchase fee).

  In the first embodiment, as described above, the predetermined period is, for example, 24 hours, one week, one month, three months (period for each season), or the like. The generation unit 230 preferably generates a correspondence relationship for each day of the week, weather, or season.

  The calculation unit 240 is based on the operations of the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160, and is at least one of a purchase price of power supplied from the grid and a sale price of power provided to the grid. As a solution, an optimal solution is calculated by searching for a plurality of combinations. Specifically, the calculation unit 240 calculates an optimal solution for each unit time using an objective function shown below.

  Here, cell_power (t) indicates the trading power in unit time t. When cell_power (t) is a positive value, a reverse power flow is performed on the system, and cell_power (t) When is a negative value, power is supplied from the grid. cell_unit_price (t) indicates the unit price of the sold power in unit time t, and buy_unit_price (t) indicates the unit price of purchased power in unit time t. Here, the unit time t is, for example, the minimum time interval at which charging / discharging of the power storage device can be switched.

  Here, the parameter is, for example, the unit price of power supplied from the grid. Alternatively, the parameter is, for example, the sales unit price of power provided to the grid. Alternatively, the parameter is the unit price of fuel gas purchase.

  Here, as shown in FIG. 8, the elements applied to the objective function are the operation of the PV unit 130 (PV operation), the operation of the storage battery unit 140 (operation of the storage battery), and the operation of the fuel cell unit 150 (operation of the fuel cell). Operation) and hot water storage unit 160 operation (hot water storage unit operation).

  The operation of the PV unit 130 is an operation predicted based on the PV power generation amount prediction information. For example, the PV unit 130 is controlled by the MPPT method. FIG. 8 illustrates a case where the operation of the PV unit 130 is three types of “AA”, “AB” (not shown in the drawing), and “AC”.

  The operation of the storage battery unit 140 is, for example, power storage, discharge, and maintenance. FIG. 8 illustrates a case where the operation of the storage battery unit 140 has three types of “BA”, “BB” (not shown in the drawing), and “BC”.

  The operation of the fuel cell unit 150 is an operation predicted based on the energy consumption prediction information. For example, the fuel cell unit 150 is controlled by load following control. FIG. 8 illustrates a case where the operation of the fuel cell unit 150 is of three types “CA”, “CB”, and “CC”.

  The operation of the hot water storage unit 160 is, for example, an increase in the amount of hot water storage, maintenance of the hot water storage amount, and no warming. FIG. 8 illustrates a case where the operation of the hot water storage unit 160 has three types of “DA”, “DB”, and “DC”.

In the case shown in FIG. 8, there are 81 types (3 ⁴ ) of combinations of elements. The calculation unit 240 applies all combinations to the objective function in a brute force manner, and identifies combinations of elements (operations) that constitute the maximum value (optimum solution) of “Sell_price (t)”.

  Here, Sell_price (t) may be considered as a purchase fee for power supplied from the grid, or may be considered as a charge for selling power provided to the grid.

  In the first embodiment, the calculation unit 240 calculates the optimal solution in the case of generating a correspondence between the calculation time of the optimal solution and the calculation accuracy of the optimal solution in addition to the case of actually controlling each device. It should be noted.

  The control unit 250 controls the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160. The control unit 250 controls the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160 based on the elements (operations) that constitute the optimal solution calculated by the calculation unit 240.

  In the first embodiment, the control unit 250 includes a specifying unit that specifies the time length of the optimum unit time from the correspondence (for example, the table shown in FIG. 7) generated for each unit time having a different time length. Configure. In addition, the control unit 250 configures a selection unit that selects a unit time having an optimal unit time length as a unit time used for the calculation of the optimal solution.

  Specifically, it is preferable that the control unit 250 basically selects a unit time with the highest calculation accuracy of the optimal solution. For example, in the table shown in FIG. 7, the control unit 250 preferably selects a unit time corresponding to the optimization level 7.

  Alternatively, the control unit 250 may select a unit time in which the calculation accuracy of the optimal solution is equal to or greater than a predetermined threshold and the rate at which the calculation accuracy increases with respect to the increase in the calculation time (the increase rate of the calculation accuracy) is high. . For example, in the table shown in FIG. 7, since the rate of increase in calculation accuracy changes linearly, it is preferable that the control unit 250 selects a unit time corresponding to the optimization level 7.

  Alternatively, when the processing load of the HEMS 200 is equal to or greater than the threshold, the control unit 250 selects a unit time having a time length shorter than the optimum unit time as the unit time used for the calculation of the optimal solution. For example, in the table shown in FIG. 7, the control unit 250 preferably selects a unit time corresponding to an optimization level of 6 or less when the processing load of the HEMS 200 is equal to or greater than a threshold.

  In such a case, it is preferable that the control unit 250 selects a unit time having a shorter calculation time as the processing load of the HEMS 200 is higher.

  Of course, the arithmetic unit 240 described above calculates an optimal solution for each unit time selected by the control unit 250 in the case of actually controlling each device.

(Overview of search method)
The outline of the search method will be described below. FIG. 9 is a diagram for explaining the outline of the search method according to the first embodiment. The first embodiment exemplifies a case where an optimal solution is calculated for each predetermined period constituted by a plurality of unit times. That is, the unit time is a period obtained by dividing a predetermined period.

For example, as shown in FIG. 9, a case will be described in which there are three types of branching of elements of each device in each unit time (t1, t2, t3, t4...). Specifically, in FIG. 9, the operation (element) of each apparatus is represented by A, B, and C. For example, in the unit time t2, the operation (element) of each device is A ₂ , B ₂ , C ₂ . In such a case, the arithmetic unit 240, as a general rule, calculates optimal solutions for all combinations of elements using the above-described objective function.

  However, the search for the combination of elements that do not satisfy the constraints of the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160 may be omitted.

  Note that the calculation unit 240 may calculate an optimal solution for all combinations of elements using an algorithm such as a Viterbi algorithm that guarantees the same performance as the brute force search method.

  In the first embodiment, the constraint condition of each device is that the state of each device corresponding to each element does not exceed the capability of each device. Specifically, for example, the power generation amount of PV 131 does not violate the PV power generation amount prediction information, the power storage amount of storage battery 141 is not smaller than the threshold, and the power generation amount of fuel cell 151 does not exceed the threshold. The condition is that the amount of hot water stored in the hot water storage unit 160 is not smaller than the threshold value. In such a case, the search for a combination of elements including elements that do not satisfy the constraint is omitted.

(Control method)
Hereinafter, a control method according to the first embodiment will be described. 10 and 11 are flowcharts showing the control method according to the first embodiment. Specifically, FIG. 10 and FIG. 11 are flowcharts showing the operation of the HEMS 200.

  First, the case of generating the correspondence between the calculation time of the optimal solution and the calculation accuracy of the optimal solution will be described with reference to FIG.

  As shown in FIG. 10, in step 10, the HEMS 200 sets a unit time. Here, it should be noted that the unit time is set in ascending order of time length.

  In step 20A, the HEMS 200 sets each element (operation) for each unit time. The HEMS 200 repeats the processing from step 30 to step 50 until the optimal solution is calculated for all the unit times included in the predetermined period.

  In step 30, the HEMS 200 calculates an optimal solution every unit time.

  In step 40, the HEMS 200 determines whether or not the calculation of the optimal solution is the first loop. If the determination result is “YES”, the HEMS 200 proceeds to the process of step 50. On the other hand, when the determination result is “NO”, the HEMS 200 proceeds to the process of Step 20B and returns to the process of Step 20A.

  In step 50, the HEMS 200 determines whether or not the accuracy of the optimum solution has deteriorated with respect to other time lengths. If the determination result is “YES”, the HEMS 200 proceeds to the process of step 70. On the other hand, when the determination result is “NO”, the HEMS 200 proceeds to the process of Step 20B and returns to the process of Step 20A.

  Here, since the unit time is set in order of increasing time length, the unit time in which the calculation accuracy of the optimal solution deteriorates is excluded from the generation of the correspondence relationship even though the calculation time of the optimal solution is long.

  In step 60, the HEMS 200 records the time length of the unit time, the calculation time of the optimal solution, and the optimal solution.

  In step 70, the HEMS 200 confirms whether or not the processing in steps 10 to 60 has been completed for all time lengths. If the determination result is “YES”, the HEMS 200 proceeds to the process of step 80. On the other hand, when the determination result is “NO”, the HEMS 200 returns to the process of step 10.

  In Step 80, the HEMS 200 generates a correspondence relationship between the calculation time of the optimal solution and the calculation accuracy of the optimal solution based on the information recorded in Step 60.

  Secondly, a case of actually controlling each device will be described with reference to FIG.

  As shown in FIG. 11, in step 110, the HEMS 200 collects information such as the load of the HEMS 200. The load of the HEMS 200 may be the amount of information to be processed by the HEMS 200, or may be a processing delay of the HEMS 200.

  In step 120, the HEMS 200 selects an optimization level (unit time) based on the information collected in step 10.

  In step 130, the HEMS 200 calculates an optimal solution for each unit time selected in step 20, using the objective function described above.

  In step 140, the HEMS 200 controls each device based on the elements (operations) constituting the optimal solution.

(Function and effect)
In the first embodiment, the control unit 250 generates a correspondence relationship between the calculation time of the optimal solution and the calculation accuracy of the optimal solution for each unit time having a different time length. Therefore, it is possible to select the time length of the unit time for calculating the optimum solution while referring to the correspondence relationship. As a result, it is possible to achieve both suppression of increase in the amount of calculation and calculation accuracy of the optimal solution.

[Other Embodiments]
Although the present invention has been described with reference to the above-described embodiments, it should not be understood that the descriptions and drawings constituting a part of this disclosure limit the present invention. From this disclosure, various alternative embodiments, examples and operational techniques will be apparent to those skilled in the art.

  In the embodiment, the HEMS 200 is exemplified as the control device. However, the embodiment is not limited to this. The control device may be the CEMS 20 or the smart server 40. Alternatively, the control device may be a BEMS (Building Energy Management System) or a FEMS (Factor Energy Management System).

  In the embodiment, the customer 10 includes a PV unit 130, a storage battery unit 140, a fuel cell unit 150, and a hot water storage unit 160. However, the consumer 10 may have any one of the PV unit 130, the storage battery unit 140, the fuel cell unit 150, and the hot water storage unit 160.

  DESCRIPTION OF SYMBOLS 10 ... Consumer, 20 ... CEMS, 30 ... Substation, 31 ... Distribution line, 40 ... Smart server, 50 ... Power plant, 51 ... Transmission line, 60 ... Network, 100 ... Energy management system, 110 ... Distribution board, DESCRIPTION OF SYMBOLS 120 ... Load, 130 ... PV unit, 131 ... PV, 132 ... PCS, 140 ... Storage battery unit, 141 ... Storage battery, 142 ... PCS, 150 ... Fuel cell unit, 151 ... Fuel cell, 152 ... PCS, 160 ... Hot water storage unit, 200 ... HEMS, 210 ... reception unit, 220 ... transmission unit, 230 ... generation unit, 240 ... calculation unit, 250 ... control unit

Claims (5)

A control device for controlling a distributed power source, a power storage device or a heat storage device,
A combination of a plurality of elements with the operation of the distributed power source, the power storage device or the heat storage device as an element, and at least one of a purchase fee of power supplied from the grid and a sale fee of power provided to the grid as a solution By calculating the calculation unit for calculating the optimal solution for each unit time obtained by dividing the predetermined period,
A control apparatus comprising: a generation unit that generates a correspondence relationship between the calculation time of the optimal solution and the calculation accuracy of the optimal solution for each unit time having a different time length.   The control device according to claim 1, wherein the generation unit generates the correspondence relationship for each day of the week, weather, or season. Among the correspondences generated for each unit time having a different time length, a specifying unit that specifies the time length of the optimal unit time;
The control apparatus according to claim 1, further comprising a selection unit that selects a unit time having a time length of the optimum unit time as a unit time used for the calculation of the optimum solution.   The selection unit selects a unit time having a time length shorter than a time length of the optimal unit time as a unit time used for the calculation of the optimal solution when a processing load of the calculation unit is equal to or greater than a threshold value. The control device according to claim 3. A control method for controlling a distributed power source, a power storage device or a heat storage device,
For each unit time obtained by dividing a predetermined period, the operation of the distributed power source, the power storage device or the heat storage device is an element, and the purchase price of power supplied from the grid and the sale of power provided to the grid Calculating an optimal solution using at least one of the charges as a solution;
A control method comprising: generating a correspondence relationship between the calculation time of the optimal solution and the calculation accuracy of the optimal solution for each unit time having a different time length.

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