JP2020043634A - Electric power transaction amount optimizing device - Google Patents

Abstract

To provide an electric power transaction amount optimizing device capable of calculating an electric power transaction amount optimizing a profit by electric power transactions in an entire group including electric vehicles and consumers scattered in a predetermined area.SOLUTION: The present invention relates to an electric power transaction amount optimizing device 1 defining a group including electric vehicles and consumers scattered in a predetermined area as a target. On the basis of a constraint condition meeting an electric power demand of an electric vehicle in an electric power transaction with which the electric vehicle is associated, a constraint condition meeting an electric power demand of a consumer in an electric power transaction with which the consumer is associated, and a constraint condition of an electric power transaction enabled amount which is generated when the electric vehicle and the consumer perform an electric power transaction with an electric power transaction partner by using a power transmission/distribution network in the predetermined area, optimization calculation is performed with maximization of a profit by the electric power transaction in the entire group defined as a target function, and an electric power transaction amount for the electric vehicle and the consumer in the group to transact with the electric power transaction partner is calculated.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a power transaction amount optimization device for a group including electric vehicles and consumers scattered in a predetermined area.

  2. Description of the Related Art In recent years, a technology for managing power transactions performed between an electric vehicle, a solar power generation device, a consumer, and a power system has been known.

  For example, Patent Literature 1 discloses a method of managing the charge / discharge amount of an electric vehicle that focuses on power transactions between an electric vehicle owned by a customer and an electric power system.

  Further, for example, Patent Document 2 discloses that the degree of utilization of a solar power generation device is increased by procuring electric power for charging an electric vehicle operated in a predetermined region from a solar power generation device installed in a predetermined region as much as possible. A method for enhancing is disclosed.

JP 2011-50240 A JP-A-2006-134160

  By the way, it is important to consider the profits of the entire group from the power transaction when drafting the planned value of the power transaction amount for the group including the electric vehicles and the consumers scattered in the predetermined area.

  In view of the above, the present invention provides an electric power trading amount optimizing device capable of calculating an electric power trading amount that maximizes profits from electric power trading of an entire group including electric vehicles and consumers scattered in a predetermined area. With the goal.

  The present embodiment is an electric power transaction amount optimization device for a group including electric vehicles and consumers scattered in a predetermined area, and a constraint that satisfies the electric demand of the electric vehicles in electric power transactions involving the electric vehicles. A condition, a constraint condition that satisfies the power demand of the customer in the power transaction involving the customer, and an electric power generated when the electric vehicle and the customer perform power transaction with a power trading partner using the transmission and distribution network in the predetermined area. Based on the constraints of the tradable amount, perform an optimization calculation with an objective function of maximizing profits from power trading of the entire group, and the electric vehicle and the consumer in the group are able to communicate with the power trading partner. Calculate the amount of power traded.

  Further, in the electric power transaction amount optimizing device, the electric vehicles capable of electric power transaction within the group based on the information of the scheduled parking time and the parking position of the electric vehicle and the position information of the customer stored in the storage device. It is preferable to select a customer and calculate the power transaction amount for the selected electric vehicle and the customer.

  In the power transaction amount optimization device, the group includes the electric vehicle and a photovoltaic power generation device that distributes power to the customer, and the three constraint conditions and a power transaction related to the photovoltaic power generation device. In the method, it is preferable that the optimization calculation is performed based on a constraint condition regarding a power generation amount of the solar power generation device.

  Further, it is preferable that in the electric power transaction amount optimizing device, the constraint condition of the electric power transaction possible amount is set based on allowable electric energy information of a power transmission and distribution network stored in a storage device.

  Further, in the power transaction volume optimization device, it is preferable that the optimization calculation uses a linear programming method.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to calculate the electric power transaction amount which maximizes the profit by the electric power transaction of the whole group including the electric vehicle and consumer scattered in a predetermined area.

It is a block diagram showing an example of composition of a power transaction volume optimization device concerning this embodiment. It is a flowchart explaining the processing content of an electric power transaction model preparation part. (A) ~ (c) is a diagram showing the EV _{v i}, customer _{{d i}, PV {pv} i} possible power trading around the power counterparty. It is a flowchart explaining the processing content of a transaction constraint model preparation part. Is a diagram illustrating a transmission and distribution network for use with the EV {v _1} and power trading. Is a diagram illustrating a transmission and distribution network for use with the EV {v _1} and power trading. Is a diagram illustrating a transmission and distribution network for use with the EV {v _1} and power trading. Is a diagram illustrating a transmission and distribution network for use with the EV {v _1} and power trading.

  FIG. 1 is a block diagram illustrating an example of a configuration of the power transaction amount optimizing device according to the present embodiment. The power trading amount optimizing device 1 shown in FIG. 1 includes a processing unit 2 including a CPU and the like, and a storage unit 3 including a ROM and a RAM. The processing unit 2 includes, as functional blocks realized by executing the optimization program stored in the storage unit 3, a condition setting unit 10, a power transaction model creation unit 12, a transaction constraint model creation unit 14, an optimization calculation unit 16 is provided. An input device 20 and a display device 22 are connected to the power trading amount optimizing device 1 shown in FIG. The input device 20 is a user interface for receiving an input operation from a user, and is, for example, a mouse or a keyboard. The display device 22 is a user interface for displaying information, calculation results, and the like output by the electric power trading volume optimization device 1, and is, for example, a display.

  The storage unit 3 is connected to the processing unit 2 so as to be accessible, and includes an optimization program, an electric vehicle database (hereinafter, an EV database 24), a customer database 26, a solar power generation device database (hereinafter, a PV database 28), and a system database. 30 is stored. The various databases may be stored in a storage device of an external server, for example. In this case, the power trading amount optimizing device 1 is connected to the external server by a communication unit such as the Internet, and the processing unit 2 is configured to be able to access a storage device of the external server. .

  The EV database 24 includes information on the scheduled parking time and the scheduled parking position of the EV, information on the required remaining battery level at the start of EV traveling, information on the battery capacity of the EV battery, information on the charge / discharge efficiency of the EV battery, and the like. .

  The customer database 26 includes position information of the customer, position information of the charger / discharger owned by the customer, information of the power demand of the customer, and the like.

  The PV database 28 includes PV position information, PV power generation amount information, and the like.

  The system database 30 includes information on the allowable amount of reverse tide power in the distribution network, information on the allowable amount of reverse tide power in the transmission network, information on the allowable entrusted transmission amount between the distribution networks, information on the allowable entrusted transmission amount between the distribution networks, and the power system. The information includes information on power purchase unit price, information on PV power purchase unit price of the power system, information on power sale unit price of the power system, and information on unit price of a transmission fee between distribution networks.

  The respective information included in the EV database 24, the consumer database 26, and the PV database 28 is obtained from EV owners, consumers, and PV owners in a group including EVs, consumers, and PVs scattered in a predetermined area. Information acquired in advance and included in the grid database 30 is information received from a grid operator of a power transmission and distribution network used for electric power transactions between EVs, consumers, and PVs.

  Hereinafter, each functional unit of the processing unit 2 will be described.

  The condition setting unit 10 receives data input of a period and a region where the optimization calculation is performed.

  FIG. 2 is a flowchart illustrating the processing performed by the power trading model creation unit. The power transaction model creation unit 12 refers to the EV database 24, the customer database 26, the PV database 28, and the system database 30, and refers to the location information of the customer, the location information of the PV, the scheduled parking time of the EV, and the information of the parking location. , An EV, a customer, and a PV included in a period and a region (predetermined region) input to the condition setting unit are selected. Is selected (step S10).

  The power transaction model creation unit 12 refers to the customer database 26, collates the position information of the charger / discharger owned by the selected customer with the information on the estimated parking time and the parking position in the selected EV, At each time, a charge / discharge device to which the EV can be connected is selected (step S12). For example, a charge / discharge device to which the EV can be connected is selected based on the distance between the position of the charge / discharge device and the parking position of the EV.

The power trading model creation unit 12 creates a variable (hereinafter, a power trading variable) determined by the optimization calculation (Step S14). The power trade variable indicates the amount of power traded between the EV, the customer, the PV, and the power system selected in step S10. The power trading variables can be obtained by listing the power trading partners that can perform power trading with each other, centering on the selected EV, the selected customer, and the selected PV. For example, selecting the power system _{g 1 ··· g o}, chosen the consumer is _{d 1 ··· d p}, selected the EV is _{v 1 ··· v q}, selected the PV is for _{pv 1 ··· _{pv r},} the following power transaction variables are created.

<Electricity trading variables to create around the EV _{{v i}>}
3 (a) is a diagram showing a power tradable power counterparties around the EV {v _i}. Power counterparty of FIG 3 (a) EV shown in _{{v i}} is the electric power system _{{g m}, PV {pv} l}, customer _{d k}, is EV _{{v j}.} In this case, the amount of power at time t is EV _{{v i}} be purchased from the electric power system _{{g m}: Xg m v} i (t) (i = 1 ··· q, m = 1 ··· o), time watt EV _{{v i}} to t to sell electricity to the power grid _{{g m}: Xv i g} m (t) (i = 1 ··· q, m = 1 ··· o), EV at time t watt _{{v i}} purchase from _{PV {pv l}: Xpv l} v i (t) (i = 1 ··· q, l = 1 ··· r), is EV _{{v i}} at time t electric energy to sell electricity to consumers _{{d k}: Xv i d} k (t) (i = 1 ··· q, k = 1 ··· p), EV at time t _{{v i}} is EV {v electric energy purchased from _{j}: Xv j v i (} t) (i = 1 ··· q, j = 1 ··· q, i ≠ j), EV {v i} is EV at time t _{{v j} electric energy to sell electricity to _{the}: Xv i v j (t} ) (i = 1 ·· q, j = 1 ··· q, i ≠ j) is the power trading variables.
However, even if the EV is running or the EV is parked at time t, if there is no connectable charger / discharger at the parking position, the electric power transaction between the EV and the electric power trading partner is impossible. Therefore, in step S12, at times other than the time when the EV selects a connectable charger / discharger, the power transaction variable becomes 0.

<Power trading variables created around the customer {d _k }>
FIG. 3 (b) is a diagram illustrating power trading partners who can trade power centering on the customer {d _k }. Power counterparty customers shown in FIG. 3 (b) _{{d k}} is the electric power system _{{g m},} a PV {pv l}, EV { v i}. In this case, the electric energy purchased by the customer {d _k } from the power system {g _m } at the time t: Xg _m d _k (t) (k = 1... P, m = 1. Electric energy purchased by customer {d _k } from PV {pv _l } at time t: Xpv _l d _k (t) (k = 1... P, l = 1... R), demand at time t amount of power house _{{d k}} to buy from _{EV {v i}: Xv i} d k (t) (k = 1 ··· p, i = 1 ··· q) is the power trading variables.
However, as described above, at step S12, the time other than the time when the EV has selected discharge unit connectable, the Xv i d _k power trading variable 0 _(t).

<Power trading variables created around PV {pv _l }>
FIG. 3 (c) is a diagram showing power trading partners capable of power trading centering on PV {pv _l }. Power counterparty PV {pv _l} shown in FIG. 3 (c), the power system _{g m}, is EV _{v i}, customer _{{d k}.} In this case, the amount of power sold from the PV {pv _l } to the power system {g _m } at time t: Xpv _l g _m (t) (l = 1... R, m = 1... O), electric energy to sell electricity from PV {pv _l} at time t to the _{EV {v i}: Xpv l} v i (t) (l = 1 ··· r, i = 1 ··· q), PV at time t The amount of power sold from {pv _l } to the customer {d _k }: Xpv _l d _k (t) (l = 1... R, k = 1... P) is a power trading variable.
However, as described above, at step S12, the time other than the time when the EV has selected discharge unit connectable, the Xpv l v power trading variable 0 i _(t).

  FIG. 4 is a flowchart illustrating the processing content of the transaction constraint model creation unit. The transaction constraint model creating unit 14 creates a constraint condition that satisfies the electric power demand of the EV in the electric power transaction involving the EV (FIG. 3A) (Step S20), and the electric power transaction involving the customer (FIG. 3B). In step S22, a constraint condition that satisfies the power demand of the consumer is created (step S22), and in the power transaction involving the PV (FIG. 3C), a constraint condition regarding the power generation amount of the PV is created (step S24). Then, a constraint condition is created for the amount of power that can be traded when the PV trades with the power trading partner using the power transmission and distribution network in the predetermined area (step S26). Hereinafter, each step will be described.

<Step S20>
Trading constraints model creation unit 14, from the EV database 24, information of necessary remaining battery power at the start of the EV travel _(L vi _(t)), the battery capacity of the EV information ^{_{(ΔS inmax vi, ΔS outmax vi}} , S max vi , ^S _min vi), charge and discharge efficiency of information (eta ⁱⁿ _vi battery of EV, acquires eta ^out _vi), satisfies the EV power demand in EV _{{v i}} power trading involving shown in FIG. 3 (a) Create constraints. Specifically, it is represented by the following equations (1) to (5).

In the formula _{(1) ~ (5),} S vi (t): the amount of charge of the battery at time t of the ^{_{EV {v i}, η in}} vi: charging efficiency of the battery of the ^{_{EV {v i}, η out}} vi: EV _{{v i}} battery discharge ^efficiency, ΔS inmax _vi: chargeable amount per unit time battery ^{_{EV {v i}, ΔS outmax}} vi: dischargeable per unit time battery EV _{{v i}, ^{S max vi: EV {v i}} } charge amount of the maximum value of the ^{_{cell, S min vi: EV {v}} i} charge amount minimum value of the _{battery, L} vi (t): EV at time t _{v i} Power demand (running load).

In Expressions (1) to (5), Expression (1) represents a constraint based on the charge amount S _vi (t) of the battery, and Expression (2) is based on the chargeable amount per unit time ΔS ^inmax _vi of the battery. Equation (3) represents a constraint based on the dischargeable amount ΔS ^outmax _vi of the battery per unit time, and equation (4) represents a constraint based on the upper and lower limits of the battery charge S _vi (t). represents the formula (5) represents a constraint that is based on the power demand of EV _{{v i}} (running load).

<Step S22>
The transaction constraint model creation unit 14 acquires information on the power demand of the customer from the customer database 26, and satisfies the power demand of the customer in the power transaction involving the customer {d _k } in FIG. Create constraints. Specifically, it is represented by the following equation (6). In the following equation (6), L _dk (t) means the power demand at the time t of the customer {d _k }.

<Step S24>
The transaction constraint model creation unit 14 acquires information on the amount of power generation of the selected PV from the PV database 28, and creates a constraint on the amount of power generation of the PV in the power transaction involving the PV {pv _l } in FIG. I do. Specifically, it is represented by the following equation (7). In the following equation (7), P _pvl (t): means the amount of power generation at time t of PV {pv _l }.

<Step S26>
From the system database 30, the transaction constraint model creation unit 14 obtains information on the allowable amount of reverse power in the distribution network in a predetermined area (DS _n ^out (t)) and information on the allowable amount of reverse power in the transmission network in the predetermined area (TS). _gm ^out (t)), information of allowable consignment amount of power distribution networks ^{_{(DS n in (t))}} , the allowable consignment amount of information of power transmission networks ^{_(TS gm} in _(t)) to get the, EV, demand A constraint is created on the amount of power that can be traded when a house or PV trades with a power trading partner using a power transmission and distribution network in a predetermined area. Specifically, it is represented by equations (8) to (11).

In the following equations (8) to (11), {TS _gm (gm = 1... U)}: a transmission network included in a predetermined area, {DS _n (n = 1... S)}: a predetermined area Included power grid, ID _dl {TS _dk , DS _dk }: Power grid used by customer {d _k } during power trading, ID _pvl {TS _pvl , DS _pvl }: PV {pv _l } during power trading Transmission / distribution network used, ID _vj (t) {TS _vj (t), DS _vj (t)}: Transmission / distribution network used at the time of EV {v _j } charging / discharging at time t during power trading, TS _gm ^out (t): the allowable amount of power flowing out from the power grid ^{_{TS gm, TS gm in (t}} ): the allowable amount of power flowing into the power grid ^{_{TS gm, DS n out (t}} ): allowable power that flows from the power distribution network DS _{n amount,} ^{DS n} in (t): flowing into the distribution network DS _n Means that the allowable amount of power.

In Expressions (8) to (11), Expression (8) represents a constraint based on an allowable power amount flowing out from the power transmission network TS _gm , and Expression (9) is based on an allowable power amount flowing into the power transmission network TS _gm . It represents a constraint, equation (10) represents a constraint that is based on the allowable amount of power flowing from the power distribution network DS _n, equation (11) represents a constraint that is based on the allowable amount of power flowing into the grid DS _n.

Figure 5-8 is a diagram illustrating the transmission and distribution network for use with the EV {v _1} and power trading. For example, as shown in FIG. 5, when EV {v ₁ } does not use the power transmission and distribution network and exchanges power with customers {d ₁ } and EV {v ₂ }, equations (8) to (8) are used. The restriction of (11) does not work. For example, as shown in FIG. 6, when the EV {v ₁ } trades power with the customer {d ₂ } using the power distribution network DS ₁ , the power transmission network TS ₁ , and the power distribution network DS ₂ , Since it is necessary to consider DS ₁ ^out (t) and DS ₂ ⁱⁿ (t), the constraints of Expressions (10) and (11) act. Also, as shown in FIG. 7, when the EV {v ₁ } uses the power distribution network DS ₁ and the power transmission network TS ₁ to trade power with the power system g ₁ , DS ₁ ^out (t) and TS ₁ ^out Since it is necessary to consider (t), the restrictions of Expressions (8) and (10) act. Also, as shown in FIG. 8, when EV {v ₁ } trades power with customer {d ₃ } using distribution network DS ₁ , transmission networks TS ₁ and TS ₂ , and distribution network DS _3. Needs to consider DS ₁ ^out (t), TS ₁ ^out (t), TS ₂ ⁱⁿ (t), and DS ₃ ⁱⁿ (t), so the constraints of Expressions (8) to (11) are not satisfied. Works. The above is an example. For example, if EV {v ₁ } is replaced with PV, a power transaction is performed between the customer and the EV and PV, and if the customer {d ₂ } is replaced with EV, power transmission is performed. It is an electric power transaction between EVs when a network is used.

  As described above, the combination of the constraint equations that operate may differ depending on the transmission / distribution network used between the EV, the customer, the PV, and the power trading partner. Therefore, the transaction constraint model creation unit 14 refers to the grid database 30 to select a power transmission and distribution network to be used between the EV, the customer, the PV, and the power trading partner from the jurisdiction area information, and selects the selected power transmission and distribution network. , A combination of constraint expressions to be applied is set.

  The optimization calculation unit 16 sets the objective function to maximize the profit in the power transaction of the entire group including the EV, the customer, and the PV based on the constraint conditions (Equations (1) to (11)) created above. Perform optimization calculations. For the optimization calculation, for example, a linear programming, a mixed integer programming, a non-linear programming, or the like is used, but a linear programming is preferable in terms of calculation accuracy and the like.

  The objective function in the optimization calculation is to maximize the profit (PL) in the power trading of the entire group represented by the equation (12). The revenue (PL) in the power trading of the entire group is obtained from the power selling revenue (Income, equation (13)), the system power purchasing cost (CostP, equation (14)), and the consignment cost (CostT) in the power trading within the group. , Expression (15)) and the incentive (CostI, Expression (16)) to be paid to the contractor. The incentive is a reward paid to a contractor in a group when the contractor performs a power transaction at a specific time.

In equations (13) to (15), PB _gm (t): unit price of power purchase of power system {g _m }, PBPV _gm (t): unit price of PV power purchase of power system {g _m }, PS _gm (t) : Unit price of electric power sales of the electric power system {g _m }, T _pvvivi (t): Unit price of the consignment charge between PV {pv _l } and EV {v _j }, T _pvldk (t): PV {pv _l } and demand The unit price of the consignment fee between house {d _k }, T _bidk (t): means the unit price of the consignment charge between EV {v _j } and customer {d _k }. These unit prices used in the equations (13) to (15) are information included in the system database 30 and are acquired from the system database 30 when the optimization calculation unit 16 performs the optimization calculation.

In the formula _{(16), ISv i g m} : time t incentive coefficient when EV _{{v i}} is sell electricity to the power grid _{{g m} in, IBpv l v i (t)} : the time t EV _{{v i} incentive coefficient of when} to buy from _{pV {pv l}, ISv i} d k (t): incentive coefficient when the time t is EV _{{v i}} to sell electricity to consumers _{{d k}, IBv} j v _i (t): incentive coefficient when the time t EV _{{v i}} is purchased from _{EV {v j}, IBv i} v j (t): the time t EV _{{v i}} is the EV _{{v j}} Incentive coefficient when selling electricity, IBpv ₁ d _k (t): Incentive coefficient when customer {d _k } purchases from PV {pv _l } at time t, IBv _i d _k (t): At time t purchase consumer _{{d k}} is from EV _{{v i}} Incentives factor in _{that, ISpv l g m (t)} : Incentive coefficient when sell electricity at time t from the PV {pv _l} to the system _{{g m}, ISpv l v} i (t): time t PV { incentive coefficient of time of from pv _l} to sell electricity to the _{EV {v i}, ISpv l} d k (t): at time t the incentive coefficient of time to sell electricity to the pV {consumers from pv _{l} {d k}} means.

  Each incentive coefficient is a preset numerical value.

By the optimization calculation by the optimization calculation unit 16, a power trading amount (the power trading variable set as described above) that maximizes the profit from the power trading of the entire group is calculated. In the present embodiment, the amount of power EV _{{v i}} is purchased from the electric power system _{{g m} (Xg m v} i (t)), the amount of power EV _{{v i}} is sell electricity to the power grid _{{g m} (Xv i g m (t)} ), the amount of power EV _{{v i}} purchase from _{PV {pv l} (Xpv l} v i (t)), sold to the EV _{{v i}} is the customer _{{d k}} the amount of power to electricity _{(Xv i d k (t)} ), the amount of power EV _{{v i}} is purchased from _{EV {v j} (Xv j} v i (t)), EV {v i} is EV _{{v j} amount of power the power sale _{to} (Xv i v j (t} )), the amount of power consumers is _{{d i}} be purchased from the electric power system _{{g m} (Xg m d} i (t)), customer _{{d i} } amount of power purchased from _{PV {pv l} (Xpv l} d i (t)), the amount of power consumers _{{d i}} is purchased from _{EV {v i} (Xv j} d _{i (t)), PV {} pv i} amount of power sell electricity to the power grid _{{g m}} from _{(Xpv i g m (t)} ), the power to sell electricity from PV {pv _i} to EV _{{v j}} the amount _{(Xpv i v j (t)} ), PV {pv i} from consumer electric energy to sell electricity to _{{d k} (Xpv i d} k (t)) is calculated.

  Further, in the present embodiment, since the amount of power trade at each time is calculated, it is possible to formulate a power trade plan using the amount of power trade at each time.

  The power transaction amount calculated by the optimization calculation unit, the power transaction plan using the power transaction, the profit calculated using the equations (12) to (16), and the like are output to the display device 22.

  In the present embodiment, the power transaction amount is calculated for the group including the EV, the customer, and the PV, but the PV may be excluded from the target. In this case, the term relating to PV in each equation may be omitted.

  In the present embodiment, the electric power system exemplified as one of the electric power trading partners with which the EV, the customer, and the PV trade electric power is an example of an electric power market.

DESCRIPTION OF REFERENCE NUMERALS 1 power transaction volume optimization device, 2 processing unit, 3 storage unit, 10 condition setting unit, 12 power transaction model creation unit, 14 transaction constraint model creation unit, 16 optimization calculation unit, 20 input device, 22 display device, 24 EV database, 26 customer database, 28 PV database, 30 system database.

Claims (5)

An electric power trading volume optimization device for a group including electric vehicles and consumers scattered in a predetermined area,
A constraint satisfying the power demand of the electric vehicle in the power transaction involving the electric vehicle, a constraint satisfying the power demand of the customer in the power transaction involving the customer, the electric vehicle and the customer being located in the predetermined area. Based on the constraints on the amount of power tradeable that occurs when power trading with a power trading partner using the power transmission and distribution network, perform an optimization calculation with the objective function to maximize profits from power trading for the entire group, An electric power trading amount optimizing device, wherein the electric vehicle and the customer in a group calculate an electric power trading amount for trading with the electric power trading partner.   Based on the information on the scheduled parking time and parking position of the electric vehicle and the position information of the customer stored in the storage device, an electric vehicle capable of performing power transaction within the group, a customer is selected, and the selected electricity is selected. The power transaction amount optimizing device according to claim 1, wherein the power transaction amount is calculated for a car and a consumer. The group includes the electric vehicle, a solar power generation device that distributes electric power to the consumers,
3. The optimization calculation according to claim 1, wherein the optimization calculation is performed based on the three constraints and a constraint on a power generation amount of the photovoltaic power generation device in a power transaction involving the photovoltaic power generation device. 4. A power transaction volume optimization device as described.   The electric power transaction according to any one of claims 1 to 3, wherein the constraint condition of the electric power transmissible amount is set based on allowable electric energy information of a power transmission and distribution network stored in a storage device. Quantity optimization device. The power transaction amount optimization device according to any one of claims 1 to 4, wherein the optimization calculation uses a linear programming method.

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