JP6725380B2 - Optimization calculation device, optimization calculation method, and program - Google Patents

Description

Embodiments of the present invention relate to an optimization calculation device, an optimization calculation method, and a program.

By fully liberalizing electricity retailing, it has become possible for each business operator to flexibly set conditions such as the electricity charge system. The flow of such liberalization is not limited to electric power, and expansion of liberalization to other infrastructure such as gas is being considered. Negawatt trading is expected to start on the power exchange in the future. Therefore, various preconditions for studying energy management are diversifying. Against this background, it is required to realize optimal energy management that flexibly responds to changes in the above-mentioned preconditions.

There are various technologies for deriving an optimal operation plan of equipment related to energy operation in order to realize optimal energy operation. For example, there is a technique of calculating an optimum solution that optimizes the evaluation index value under a predetermined constraint condition expression. In order to facilitate the derivation of the optimum solution, an equation such as a device characteristic equation simplified by a method such as linear approximation is generally used. Therefore, there was room for improvement to obtain a more appropriate solution.

JP, 2005-56104, A

The problem to be solved by the present invention is to provide an optimization calculation device, an optimization calculation method, and a program that can obtain a more appropriate solution.

The optimization calculation device of the embodiment has an evaluation index value calculation unit, an evaluation index function calculation unit, and a solution determination unit. A plurality of combinations of a first solution that brings the evaluation index value that changes according to the set value closer to the optimum under the constraint condition expression including the first function and the set value are input to the evaluation index value calculation unit. It The evaluation index value calculation unit includes a first value, which is the evaluation index value corresponding to the constraint condition expression and the setting value when the first function is changed to a second function, and the setting value. And a second value which is the evaluation index value when is changed for each of the combinations. The evaluation index function calculation unit calculates, for each of the combinations, an evaluation index function that indicates the relationship between the set value and the evaluation index value and that has the first value and the second value. The solution determination unit calculates a position of an intersection of the evaluation index functions corresponding to each of the plurality of combinations. The solution determination unit, for each range of the set value divided by the set value corresponding to the intersection, based on the positional relationship of the evaluation index function, a second solution that brings the evaluation index value closer to the optimum value. decide.

The block diagram which shows the structure of the system containing the optimization calculation apparatus of 1st Embodiment. The figure which shows the example of the control object apparatus of 1st Embodiment. The block diagram which shows the structure of the optimization calculation apparatus of 1st Embodiment. 5 is a flowchart showing a procedure of processing performed by the optimization computing device according to the first embodiment. The figure which shows the relationship of the setting value and evaluation index value of 1st Embodiment. The figure which shows the transition of the optimal solution of the purchased electric energy according to the change of the setting value of 1st Embodiment. The block diagram which shows the structure of the system containing the optimization calculation apparatus of 2nd Embodiment. The block diagram which shows the structure of the optimization calculation apparatus of 2nd Embodiment. The flowchart which shows the procedure of the process by the optimization calculation apparatus of 2nd Embodiment. The figure which shows the change of the setting value of 2nd Embodiment typically. The figure which shows the change of the setting value of 2nd Embodiment typically.

Hereinafter, an optimization calculation device, an optimization calculation method, and a program according to the embodiments will be described with reference to the drawings.

(First embodiment)
FIG. 1 shows the configuration of a system including the optimization calculation device 6 according to the first embodiment. As shown in FIG. 1, a controlled object device 2, a local control device 3, a central monitoring system 4, a solution calculation device 5, and an optimization calculation device 6 are arranged in a building 1 that is a target of energy operation. To be done.

The controlled device 2 includes at least one of an energy consumption device, an energy supply device, and an energy storage device. The local control device 3 is connected to the control target device 2 and controls the operating state of the control target device 2. For example, the local control device 3 controls the states of the control target device 2, such as starting, stopping, and outputting. The central monitoring system 4 monitors the control by the local control device 3. The solution calculation device 5 calculates a quasi-optimal solution that brings the evaluation index value closer to the optimum value under the constraint condition expression. The optimization calculation device 6 calculates a more appropriate optimum solution based on the suboptimal solution calculated by the solution calculation device 5.

FIG. 2 shows an example of the controlled device 2. An energy consuming device is a device that consumes the supplied energy. For example, the air conditioner 211 and each heat source device (the electric refrigerator 203 and the absorption chiller/heater 204) are included in the energy consuming device. An energy supply device is a device that supplies energy to an energy consuming device and an energy storage device. For example, PV (photovoltaic power generation device) 201 and CGS (cogeneration system) 202 are included in the energy supply equipment. An energy storage device is a device that stores supplied energy. For example, the storage battery 200 and the heat storage tank 205 are included in the energy storage device.

The above configuration is an example. The introduction form of the optimization calculation device 6 is not limited to the above example.

FIG. 3 shows the configuration of the optimization calculation device 6. As shown in FIG. 3, the optimization calculation device 6 includes an evaluation index value calculation unit 10, an evaluation index function calculation unit 11, and a solution determination unit 12.

A plurality of combinations of a suboptimal solution (first solution) that brings an evaluation index value that changes according to a set value close to the optimum under a constraint condition expression that includes a first function, and an evaluation index value calculation unit Input to 10. The evaluation index value calculation unit 10 calculates a first value, which is an evaluation index value corresponding to the constraint condition expression and the set value when the first function is changed to the second function, for each of the above combinations. Further, the evaluation index value calculation unit 10 calculates a second value, which is an evaluation index value when the set value is changed, for each of the above combinations.

The evaluation index function calculation unit 11 calculates an evaluation index function that shows the relationship between the set value and the evaluation index value and has the first value and the second value for each of the above combinations. The solution determination unit 12 calculates the position of the intersection of the evaluation index functions corresponding to each of the plurality of combinations. Further, the solution determination unit 12 is an optimum solution (second solution) that brings the evaluation index value close to the optimum value based on the positional relationship of the evaluation index function for each range of the setting values divided by the setting value corresponding to the intersection. To decide.

The optimization computing device 6 may read the program and execute the read program. That is, the function of the optimization calculation device 6 may be realized by software. This program includes instructions that define the operations of the evaluation index value calculation unit 10, the evaluation index function calculation unit 11, and the solution determination unit 12. This program may be provided by a "computer-readable recording medium" such as a flash memory. Further, the above-mentioned program may be transmitted from the computer having a storage device or the like in which the program is stored, to the optimization calculation device 6 via a transmission medium or by a transmission wave in the transmission medium. The "transmission medium" for transmitting the program is a medium having a function of transmitting information, such as a network (communication network) such as the Internet or a communication line (communication line) such as a telephone line. Moreover, the above-mentioned program may implement|achieve a part of function mentioned above. Further, the above-mentioned program may be a difference file (difference program) that can realize the above-mentioned functions in combination with a program already recorded in the computer.

An example of processing by the solution calculation device 5 will be described. In the following example, the solution calculation device 5 calculates a quasi-optimal solution that minimizes the evaluation index value F defined by the objective function of Expression (1). Equations (2) and (3) are constraint equations.

E _C is the unit price of purchased power [yen/kWh]. GAS _C is a gas unit price [yen/kWh]. E _CGS is the CGS rated power generation [kWh/unit]. E _PV is PV power generation [kWh]. GAS is the gas usage [Nm ³ ]. E _DEMAND is the power demand [kWh]. _HDEMAND is the heat demand [kWh]. X1 is the purchased power amount [kWh]. X2 is the number of CGS operating units [units]. X3 is a heat source device heat output [kWh].

The evaluation index value F in the equation (1) is a daily energy charge including an electric power charge and a gas charge. The evaluation index value F is the total of the energy charges for one hour for one day. Equation (2) is a power supply and demand balance equation. Equation (3) is a heat balance equation. X1, X2, and X3 are decision variables. The solution calculation device 5 calculates X1 to X3 that minimizes the evaluation index value F defined by the equation (1) under the condition that satisfies the constraint condition equations (2) and (3).

In the equation (2), f(X3), which is the first function, is the power consumption of the heat source device to be planned and is formulated as a function of the heat output X3 of the heat source device. When this function is approximated by a linear expression, the above example becomes a mixed integer programming problem. It is possible to derive a suboptimal solution of X1 to X3 by a commonly known solution method.

The operation of the optimization calculation device 6 will be described with reference to FIG. FIG. 4 shows a procedure of processing by the optimization calculation device 6. For example, the operation shown in FIG. 4 is periodically executed like every 5 minutes. The operation shown in FIG. 4 can be executed at any time under conditions such as when the user's manual execution is requested or when a preset event occurs. The operation of each step will be described below.

Step S1 will be described. A plurality of combinations of a sub-optimal solution and a set value when only a specific set value that is a precondition for the optimization calculation is arbitrarily changed are input from the solution calculation device 5 to the evaluation index value calculation unit 10. Here, a case corresponding to the above example will be described. For example, the changed set value (purchased power unit price) is E _C1 , E _C2 ,..., E _Cn , and the suboptimal solutions corresponding to the set values are X1 _{1 to} X3 ₁ , X1 _{2 to} X3 ₂ ,. .., X1 _{n to} X3 _n will be described. n is an integer of 2 or more. In this example, n combinations of suboptimal solutions and set values are input from the solution calculation device 5 to the evaluation index value calculation unit 10.

The evaluation index value calculation unit 10 calculates a second function f′(X3), which is a simplified representation of the simplified first function f(X3) in the calculation by the solution calculation device 5, into a first function f′(X3). It is used instead of the function f(X3). The second function f′(X3) is a function of the heat output X3 of the heat source device. A known function is used as the second function f′(X3). For example, the first function f(X3) is a linear function and the second function f'(X3) is a non-linear function. For example, the first function f(X3) and the second function f'(X3) have different orders. The second function f'(X3) more accurately represents the characteristics of the device than the first function f(X3). The evaluation index value calculation unit 10 calculates the evaluation index values F ₁ , F ₂ ,..., F _n that are the first values under the conditions of the input suboptimal solution and set value. At this time, in the equation (2), the second function f′(X3) is used instead of the first function f(X3). The evaluation index value calculation unit 10 calculates suboptimal solutions X1′ ₁ , X1′ ₂ ,..., X1′ _n that satisfy the equation (2) to which the second function f′(X3) is applied. At this time, the suboptimal solutions X2 _{1 to} X3 ₁ , X2 _{2 to} X3 ₂ ,..., X2 _{n to} X3 _n are used. The evaluation index value calculation unit 10 uses the calculated suboptimal solutions X1′ ₁ , X1′ ₂ ,..., X1′ _n as the suboptimal solutions X1 ₁ , X1 ₂ ,..., X1 _n in the equation (1). , And the evaluation index values F ₁ , F ₂ ,..., F _n are calculated. The calculated evaluation index values F ₁ , F ₂ ,..., F _n correspond to each of the n combinations of suboptimal solutions and set values.

The evaluation index value calculation unit 10 recalculates the evaluation index value (second value) when only the input specific set value is changed by the unit amount under the input conditions of the suboptimal solution. At this time, in the equation (2), the second function f′(X3) is used instead of the first function f(X3). An evaluation index value is calculated for each of the n combinations of suboptimal solutions and set values. In calculation of the evaluation index value, the quasi-optimal solution _{X1 1, X1 2, ···,} X1 quasi-optimal solution in place of _{n X1 '1, X1' 2} , ···, X1 'n are used. Further, suboptimal solutions X2 _{1 to} X3 ₁ , X2 _{2 to} X3 ₂ ,..., X2 _{n to} X3 _n are used. The evaluation index value calculation unit 10 calculates the difference between the evaluation index value (first value) before the set value changes and the evaluation index value (second value) after the set value changes. As a result, the evaluation index value calculation unit 10 calculates the amount of change ΔF ₁ , ΔF ₂ ,..., ΔF _n in the evaluation index value. Below, the amount of change in the evaluation index value is referred to as a difference index value.

Step S2 will be described. The evaluation index values F ₁ , F ₂ ,..., F _n calculated by the evaluation index value calculation unit 10 and the difference index values ΔF ₁ , ΔF ₂ ,..., ΔF _n are stored in the evaluation index function calculation unit 11. Is entered. Evaluation index function calculating section 11, a sub-optimal solution _{X1 1 ~X3 1, X1 2 ~X3} 2, ···, evaluation indicator function corresponding to _{X1 n ~X3 n S 1, S} 2, ···, S n To generate. The evaluation index functions S ₁ , S ₂ ,..., S _n correspond to each of the n combinations of suboptimal solutions and set values. The evaluation index functions S ₁ , S ₂ ,..., S _n indicate the relationship between the set value and the evaluation index value. Details will be described with reference to FIG.

FIG. 5 shows the relationship between the set value and the evaluation index value. The horizontal axis of the graph shown in FIG. 5 is a set value (purchased power unit price), and the vertical axis is an evaluation index value (energy fee). In FIG. 5, points P1, P2, and P3 are points corresponding to specific set values and evaluation index values. The point P1 corresponds to the set value E _C1 and the evaluation index value F ₁ . The point P2 corresponds to the set value E _C2 and the evaluation index value F ₂ . The point P3 corresponds to the set value E _C3 and the evaluation index value F ₃ . The evaluation index function calculation unit 11 generates an evaluation index function S ₁ that takes an evaluation index value F ₁ (first value). The evaluation index function S ₁ is an evaluation index value (second value) when the set value is changed from E _C1 by a unit amount. That is, the evaluation index function S ₁ can be defined as a straight line that passes through the point P1 and has an inclination of ΔF ₁ in FIG. Similarly, evaluation index function calculating section 11 generates an evaluation index function S ₃ taking metric function S _2, and the evaluation index value F ₃ takes the evaluation index value F _2. The evaluation index function S ₁ , the evaluation index function S ₂ , and the evaluation index function S ₃ can be defined by the following formula (4).

When the case where i in Expression (4) is 1 is described as an example, the evaluation index function S ₁ is the energy when the purchase power unit price changes in the energy operation state determined by the suboptimal solutions X1 _{1 to} X3 _1. Shows the change in charges. In the above example, the evaluation index function is defined as a linear function of the set value, but it is not limited to this.

Step S3 will be described. The solution determination unit 12 determines the optimum solution. The details will be described again with reference to FIG.

In FIG. 5, the case where the set value, which is the unit price of purchased power, is reduced from E _C1 to E _C2 will be described as an example. The sub-optimal solutions calculated by the solution calculation device 5 are X1 _{1 to} X3 ₁ to X1 ₂ It changes to the X3 _2. That is, when approximated by Equation linear expression such as simple a f (X3) in the equation (2), by quasi-optimal solution is changed from _{X1 1 ~X3} 1 to _X1 2 ～X3 _2, the energy rates Can be lowered. However, when the expression closer to the actual characteristic is used as f(X3), the evaluation index function S ₁ exists below the evaluation index function S _{2 at} the setting value E _C2 . Therefore, the optimum solution at the set value E _C2 is X1 _{1 to} X3 ₁ .

Therefore, the more appropriate optimal solutions corresponding to a certain set value are the optimal solutions X1 _i to X3 _i corresponding to the evaluation index function S _i existing at the lowest position at that set value. The point where the optimum solution changes is the intersection of the evaluation index functions S _i existing at the bottom. In the area A of FIG. 5, the evaluation index function S ₁ exists at the bottom. Area A is a range where the set value is CB1 or more. The optimum solution in the area A is X1 _{1 to} X3 ₁ . In the region B of FIG. 5, the evaluation index function S ₂ exists at the bottom. Region B is a range where the set value is CB2 or more and less than CB1. The optimum solution in the region B is X1 _{2 to} X3 ₂ . In the area C of FIG. 5, the evaluation index function S ₃ exists at the bottom. Region C is a range where the set value is less than CB2. The optimum solution in the region C is X1 _{3 to} X3 ₃ .

The solution determination unit 12 continuously changes the set value and calculates the value of each evaluation index function at each set value, thereby calculating the position of the intersection of each evaluation index function. As a result, the solution determination unit 12 calculates the boundary set value CB1 and the boundary set value CB2 that are the set values corresponding to the positions of the intersections where the optimum solution changes. The boundary set value CB1 is a set value corresponding to the intersection of the evaluation index function S ₁ and the evaluation index function S ₂ . Boundary setting value CB2 is a set value corresponding to the intersection of the metric function S ₂ and the evaluation indicator function S _3.

The solution determination unit 12 determines an optimal solution for each range of setting values divided by the boundary setting value CB1 and the boundary setting value CB2 based on the positional relationship of the evaluation index functions S ₁ , S ₂ , and S ₃ . For example, in the area A, the evaluation index function S ₁ exists below the evaluation index function S ₂ and the evaluation index function S ₃ . Therefore, the solution determination unit 12 determines the optimum solution in the area A as X1 _{1 to} X3 ₁ . In the region B, the evaluation index function S ₂ exists below the evaluation index function S ₁ and the evaluation index function S ₃ . Therefore, solution determining unit 12 determines the optimal solution in the region B to the _{X1 2 ~X3} 2. In the region C, the evaluation index function S ₃ exists below the evaluation index function S ₁ and the evaluation index function S ₂ . Therefore, the solution determination unit 12 determines the optimum solution in the area C to be X1 _{3 to} X3 ₃ .

FIG. 6 shows the transition of the optimum solution of the decision variable X1 (purchased electric energy) according to the change of the set value. The horizontal axis of the graph shown in FIG. 6 is the set value (purchased power unit price), and the vertical axis is the purchased power amount. The optimum solution in each of the areas A, B, and C has a constant value. The optimum solution in the area A is X1 ₁ . The optimum solution in the region B is X1 ₂ . The optimum solution in the region C is X1 ₃ .

In the above example, the set value is the purchase power unit price. The set value may be one of the purchase unit price of the medium to be purchased, the CO2 emission coefficient, and the primary energy conversion coefficient. The medium may be electric power, fuel, or water.

Expression (1) corresponds to the case where the set value is the purchase unit price of the purchased power. When the set value is the CO2 emission coefficient of the purchased electric power, the purchased electric power unit price (E _C ) in the formula (1) is changed to the CO2 emission coefficient of the electric power, and the gas unit price (GAS _C in the formula (1) is used. ) Is changed to the CO2 emission coefficient of gas. When the set value is the primary energy conversion coefficient of the purchased electric power, the purchased power unit price (E _C ) in the equation (1) is changed to the primary energy conversion coefficient of the electric power, and the gas unit price ( GAS _C ) is changed to the primary energy conversion factor of gas.

The set value may be a selling unit price of the medium to be sold. When the set value is the selling unit price of the medium to be sold, the formula (1) is changed to the formula (1a), and the formula (2) is changed to the formula (2a).

In Expression (1a), the variable X4 is the sales amount of the medium to be sold, and E _S is the selling unit price of the medium to be sold.

The set value may be a sale unit price of a medium to be virtually sold, which corresponds to the reduction amount of the medium to be purchased. When the purchase amount of the purchased medium decreases, it can be considered that the same amount of the purchased medium is virtually sold. When the set value is the selling unit price of the medium to be virtually sold, which corresponds to the reduction amount of the medium to be purchased, Expression (1) is changed to Expression (1b).

In the formula (1b), Baseline is a reference value indicating a usual medium purchase amount, and E _b is a selling unit price of a medium to be virtually sold.

The optimization calculation device 6 of the first embodiment can obtain a more appropriate optimal solution based on a plurality of combinations of the sub-optimal solution and the set value.

(Second embodiment)
FIG. 7 shows the configuration of a system including the optimization calculation device 6a according to the second embodiment. As shown in FIG. 7, a control target device 2, a local control device 3, a central monitoring system 4, and an optimization calculation device 6a are arranged in a building 1 that is a target of energy operation.

FIG. 8 shows the configuration of the optimization calculation device 6a. As shown in FIG. 8, the optimization calculation device 6a includes a set value change unit 20, a solution calculation unit 21, an evaluation index value calculation unit 22, an evaluation index function calculation unit 23, and a solution determination unit 24. ..

The set value changing unit 20 generates a plurality of set values while changing the set value based on a preset amount of change. The solution calculator 21 calculates, for each set value, a sub-optimal solution (first solution) that brings the evaluation index values corresponding to each of the plurality of set values closer to the optimum. A plurality of combinations of the sub-optimal solution calculated by the solution calculation unit 21 and the set values generated by the set value changing unit 20 are input to the evaluation index value calculation unit 22.

The evaluation index value calculation unit 22 is configured similarly to the evaluation index value calculation unit 10 in FIG. The evaluation index function calculation unit 23 is configured similarly to the evaluation index function calculation unit 11 in FIG. The solution determination unit 24 is configured similarly to the solution determination unit 12 in FIG.

The optimization calculation device 6a may read the program and execute the read program. This program includes instructions that define the operations of the set value changing unit 20, the solution calculating unit 21, the evaluation index value calculating unit 22, the evaluation index function calculating unit 23, and the solution determining unit 24.

The operation of the optimization calculation device 6a will be described with reference to FIG. FIG. 9 shows a procedure of processing by the optimization calculation device 6a. The points different from the operation shown in FIG. 4 will be described below.

Step S10 will be described. The set value changing unit 20 changes the set value based on a preset change amount. For example, the amount of change is the difference between the set values before and after the set value changes. The amount of change may be the rate of change of the set value.

The step S11 will be described. The solution calculation unit 21 calculates a sub-optimal solution that brings the evaluation index value corresponding to the setting value generated by the setting value changing unit 20 closer to the optimum value. As a result, a set of sub-optimal solutions corresponding to one set value is obtained.

The step S12 will be described. One combination of the suboptimal solution and the set value is input from the solution calculation unit 21 to the evaluation index value calculation unit 22. The evaluation index value calculation unit 22 performs the same process as the process in step S1 of FIG. That is, the evaluation index value calculation unit 22 calculates the evaluation index value that is the first value under the conditions of the input suboptimal solution and the set value. The evaluation index value calculation unit 22 recalculates the evaluation index value (second value) when only the input specific set value is changed by the unit amount. The evaluation index value calculation unit 22 calculates a difference index value that is the difference between the first value and the second value.

The step S13 will be described. When the end condition is satisfied, that is, when the change in the set value is completed, the process proceeds to step S14. If the ending condition is not satisfied, that is, if the change in the set value has not ended, the process proceeds to step S10.

The processing from step S10 to step S12 is repeated until the end condition is satisfied. The setting value changing unit 20 generates a plurality of setting values by performing the processing in step S10 a plurality of times. The solution calculation unit 21 calculates a plurality of suboptimal solutions by performing the process in step S11 a plurality of times. The evaluation index value calculation unit 22 calculates the evaluation index value and the difference index value corresponding to each of the plurality of combinations of the sub-optimal solution and the set value by performing the process in step S12 a plurality of times.

The step S14 will be described. The evaluation index function calculation unit 23 performs the same process as the process in step S2 of FIG. That is, the evaluation index function calculation unit 23 generates an evaluation index function corresponding to each of a plurality of combinations of the suboptimal solution and the set value.

The step S15 will be described. The solution determination unit 24 performs the same process as the process in step S3 of FIG. That is, the solution determination unit 24 calculates the position of the intersection of each evaluation index function. The solution determination unit 24 calculates a boundary setting value corresponding to the position of the intersection at which the optimum solution changes. The solution determination unit 24 determines an optimum solution for each range of setting values separated by the boundary setting value based on the positional relationship of each evaluation index function.

The change in the set value will be described with reference to FIGS. 10 and 11. FIG. 10 schematically shows changes in set values when the controlled device 2 does not include energy storage devices such as a storage battery and a heat storage tank. FIG. 11 schematically shows changes in set values when the controlled device 2 includes energy storage devices such as a storage battery and a heat storage tank. The horizontal axis of the graphs shown in FIGS. 10 and 11 is the time, and the vertical axis is the set value (purchased power unit price). The set value is a value associated with time.

As shown in FIG. 10, the upper limit and the lower limit of the set value are set. The upper limit and the lower limit of the set value are constant. When the controlled device 2 does not include the energy storage device, the optimum solution is determined for each time. The optimal solutions at each time do not affect each other. For example, the optimum solution is determined for each time of day in the evaluation period. The set value changing unit 20 generates a plurality of set values for each of a plurality of times in the evaluation period. For example, the set value changing unit 20 generates a plurality of set values at each time by changing the set value from the upper limit by the amount of change. The set value changing unit 20 repeats the generation of the set value until the set value reaches its lower limit.

The solution calculation unit 21 calculates a suboptimal solution (first solution) for each set value for each of a plurality of times in the evaluation period. For example, in the calculation of the suboptimal solution, the formula (1c) is used instead of the formula (1). The evaluation index value F in Expression (1c) is the energy charge at a certain time. For each of the plurality of times, n sub-optimal solutions corresponding to the n set values are obtained. For example, when m times in the evaluation period are targeted, m×n suboptimal solutions are obtained. m is an integer of 2 or more.

The evaluation index value calculation unit 22 calculates the first value and the second value of the evaluation index value for each of the plurality of times in the evaluation period for each combination of the suboptimal solution and the set value. Thereby, for each of the plurality of times, n sets of the first value and the second value corresponding to the n combinations of the sub-optimal solution and the set value are obtained. For example, when m times of time in the evaluation period are of interest, m×n sets of first and second values are obtained.

The evaluation index function calculation unit 23 calculates an evaluation index function for each of a plurality of times in the evaluation period for each combination of the suboptimal solution and the set value. As a result, n evaluation index functions corresponding to n combinations of the suboptimal solution and the set value are obtained for each of the plurality of times. For example, when m times in the evaluation period are targeted, m×n evaluation index functions are obtained.

The solution determination unit 24 calculates the position of the intersection of the evaluation index function for each of the plurality of times in the evaluation period, and divides the optimum solution (second solution) by the set value corresponding to the intersection. Determine for each set value range. As a result, an optimum solution according to the set value range is obtained for each of the plurality of times. For example, when m time points in the evaluation period are targeted, m optimal solutions are obtained.

As shown in FIG. 11, in the evaluation period, the set value which is the unit price of purchased power may be different between the peak period and the other periods. For example, the evaluation period is one day, and the peak period is a daytime time period when power demand is high. The set value in the peak period is larger than the set value in the periods other than the peak period. When the controlled device 2 includes an energy storage device, it is considered that the energy storage device stores energy during a period when the unit price of purchased power is small and the energy storage device releases energy during a peak period when the unit price of purchased power is large. To be In the peak period of this usage pattern, the optimum operation plan at a certain time affects the operation plan at another time. Therefore, in the calculation of the suboptimal solution that minimizes the daily evaluation index value F defined by the equation (1), the set value in the period other than the peak period is changed and the set value in the peak period is fixed. A suboptimal solution at this time is calculated for each set value to be changed.

The set value changing unit 20 generates a plurality of set values in the evaluation period. Specifically, the setting value changing unit 20 generates a plurality of setting values in a period other than the peak period. For example, the set value changing unit 20 generates a plurality of set values at each time by changing the set value from the upper limit by the amount of change. The set value changing unit 20 repeats the generation of the set value until the set value reaches its lower limit.

The solution calculation unit 21 calculates a sub-optimal solution (first solution) in the evaluation period for each set value. For example, the solution calculation unit 21 uses the set value generated by the set value changing unit 20 as the set value in the period other than the peak period in the equation (1). Further, the solution calculation unit 21 uses the upper limit of the set value in the peak period shown in FIG. 11 as the set value in the peak period in the equation (1). As a result, n suboptimal solutions corresponding to the n set values are obtained.

The evaluation index value calculation unit 22 calculates the first value and the second value of the evaluation index value in the evaluation period for each combination of the suboptimal solution and the set value. This provides n sets of first and second values corresponding to n combinations of suboptimal solutions and setpoints.

The evaluation index function calculation unit 23 calculates an evaluation index function in the evaluation period for each combination of the suboptimal solution and the set value. As a result, n evaluation index functions corresponding to n combinations of the suboptimal solution and the set value are obtained.

The solution determination unit 24 calculates the position of the intersection of the evaluation index function, and determines the optimum solution (second solution) for each range of set values divided by the set value corresponding to the intersection. As a result, an optimum solution according to the set value range can be obtained.

The optimization calculation device 6a according to the second embodiment changes the method for generating the set value and the period for obtaining the optimum solution, depending on whether or not there is an energy storage device. Accordingly, the optimization calculation device 6a can obtain a more appropriate optimum solution depending on whether or not the energy storage device exists.

According to at least one embodiment described above, by having the evaluation index value calculation units 10 and 22, the evaluation index function calculation units 11 and 23, and the solution determination units 12 and 24, a more appropriate optimal solution is obtained. be able to.

Although some embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, replacements, and changes can be made without departing from the spirit of the invention. These embodiments and their modifications are included in the invention described in the claims and the equivalents thereof as well as included in the scope and the gist of the invention.

1... Building, 2... Control target device, 3... Local control device, 4... Central monitoring system, 5... Solution calculation device, 6, 6a... Optimization calculation device, 10, 22... Evaluation index value calculation unit 11, 23 ... evaluation index function calculation unit, 12, 24 ... solution determination unit, 20 ... set value change unit, 21 ... solution calculation unit

Claims (9)

A plurality of combinations of a first solution that makes an evaluation index value that changes according to a set value closer to an optimum under a constraint condition expression that includes a first function and a plurality of the set values are input, and the first function is A first value, which is the evaluation index value corresponding to the constraint condition expression and the setting value when changed to the second function, and a second value, which is the evaluation index value when the setting value is changed. And an evaluation index value calculation unit that calculates the value of for each combination,
An evaluation index function calculation unit that calculates the evaluation index function that shows the relationship between the set value and the evaluation index value and that takes the first value and the second value for each combination,
Calculate the position of the intersection of the evaluation index function corresponding to each of the plurality of combinations, and, for each range of the setting value divided by the setting value corresponding to the intersection, the positional relationship of the evaluation index function A solution determination unit that determines a second solution that brings the evaluation index value closer to the optimum, based on the
Optimization calculation device equipped with. The optimization calculation device according to claim 1, wherein the set value is one of a purchase unit price of a medium to be purchased, a CO2 emission coefficient, and a primary energy conversion coefficient. The optimization calculation device according to claim 1, wherein the set value is a sale unit price of a medium to be sold. The optimization calculation device according to claim 1, wherein the set value is a sale unit price of a medium to be virtually sold, which corresponds to a reduction amount of a medium to be purchased. A set value changing unit that generates a plurality of the set values while changing the set values based on a preset change amount;
A solution calculation unit that calculates, for each of the set values, the first solution that brings the evaluation index value corresponding to each of the plurality of set values closer to the optimum value;
Equipped with
The plurality of combinations of the first solution calculated by the solution calculation unit and the setting value generated by the setting value changing unit are input to the evaluation index value calculating unit. The optimization calculation device according to any one of 1. The set value is a value associated with time,
The setting value changing unit generates the plurality of setting values for each of a plurality of times in an evaluation period,
The solution calculation unit calculates, for each of the plurality of times, the first solution for each of the set values,
The evaluation index value calculation unit calculates, for each of the plurality of times, the first value and the second value for each of the combinations,
The evaluation index function calculation unit, for each of the plurality of times, calculates the evaluation index function for each of the combinations,
The said solution determination part calculates the position of the intersection of the said evaluation index function with respect to each of the said some said time, and determines the said 2nd solution for every range of the said setting value. Optimization calculator. The set value is a value associated with time,
The setting value changing unit generates the plurality of setting values in an evaluation period,
The solution calculation unit calculates the first solution in the evaluation period for each of the set values,
The evaluation index value calculation unit calculates the first value and the second value in the evaluation period for each combination,
The evaluation index function calculation unit calculates the evaluation index function in the evaluation period for each combination,
The optimization according to claim 5, wherein the solution determination unit calculates a position of an intersection of the evaluation index function in the evaluation period and determines the second solution in the evaluation period for each range of the set value. Computing device. A plurality of combinations of a first solution that brings an evaluation index value that changes according to a set value closer to an optimum value under a constraint condition expression that includes a first function and a plurality of the set values are input, and the first function is A first value, which is the evaluation index value corresponding to the constraint condition expression and the setting value when changed to the second function, and a second value, which is the evaluation index value when the setting value is changed. And an evaluation index value calculation step in which the evaluation index value calculation unit calculates the value for each combination,
An evaluation index function calculation step in which an evaluation index function calculation unit calculates an evaluation index function that shows the relationship between the set value and the evaluation index value and that takes the first value and the second value, for each combination,
The solution determination unit calculates the position of the intersection of the evaluation index function corresponding to each of the plurality of combinations, and, for each range of the set value divided by the set value corresponding to the intersection, the evaluation index. A solution deciding step of deciding a second solution that brings the evaluation index value closer to the optimum based on the positional relationship of the functions;
Optimization calculation method with. A plurality of combinations of a first solution that brings an evaluation index value that changes according to a set value closer to an optimum value under a constraint condition expression that includes a first function and a plurality of the set values are input, and the first function is A first value, which is the evaluation index value corresponding to the constraint condition expression and the setting value when changed to the second function, and a second value, which is the evaluation index value when the setting value is changed. And an evaluation index value calculation step of calculating the value of
An evaluation index function calculation step of calculating an evaluation index function for each of the combinations, which shows the relationship between the set value and the evaluation index value, and which has the first value and the second value,
Calculate the position of the intersection of the evaluation index function corresponding to each of the plurality of combinations, and for each range of the set value divided by the set value corresponding to the intersection, in the positional relationship of the evaluation index function A solution determination step of determining a second solution that brings the evaluation index value closer to the optimum based on the following:
A program that causes a computer to execute.

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