JP7107110B2 - Power trading volume optimization device - Google Patents

Description

TECHNICAL FIELD The present invention relates to an electric power trading volume optimization device for a group including electric vehicles and consumers scattered in a predetermined area.

2. Description of the Related Art In recent years, techniques for managing power transactions between electric vehicles, photovoltaic power generation devices, consumers, and power systems have been known.

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

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

Japanese Patent Application Laid-Open No. 2011-50240 JP 2016-134160 A

By the way, it is important to consider the profit from the power trading of the whole group when planning the planned value of the power trading volume for a group including electric vehicles and consumers scattered in a predetermined area.

Therefore, the present invention provides an electric power trading volume optimizing apparatus capable of calculating an electric power trading volume 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 trading volume optimization apparatus for a group including electric vehicles and consumers scattered in a predetermined area, and in electric power trading involving the electric vehicles, a constraint that satisfies the electric power demand of the electric vehicles. conditions, constraints to meet the power demand of the consumer in power transactions involving the consumer, and power generated when the electric vehicle and the consumer conduct power transactions with a power trading partner using the power transmission and distribution network in the predetermined area An optimization calculation is performed with an objective function of maximizing profits from power trading for the entire group based on the constraints on the amount of tradable amount, and the electric vehicle and the consumer in the group are aligned with the power trading partner. Calculate the power trading volume to be traded.

Further, in the power trading volume optimization device, based on the information on the scheduled parking time and parking position of the electric vehicle and the location information of the consumer stored in the storage device, the electric vehicle capable of power trading in the group Preferably, a consumer is selected, and the electric power trading volume is calculated for the selected electric vehicle and consumer.

Further, in the power trading volume optimization device, the group includes the electric vehicle and a solar power generation device that distributes power to the consumer, and the three constraints and the power trading involving the solar power generation device Preferably, the optimization calculation is performed based on a constraint condition regarding the power generation amount of the photovoltaic power generation device.

Further, it is preferable that the power transaction volume optimization device sets the constraint condition of the power transaction volume based on the allowable power volume information of the power transmission and distribution network stored in the storage device.

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

According to the present invention, it is possible to calculate the power trading volume that maximizes the profits from power trading for the entire group including electric vehicles and consumers scattered in a predetermined area.

It is a block diagram which shows an example of a structure of the power trading volume optimization apparatus which concerns on this embodiment. It is a flowchart explaining the processing content of an electric power trading model preparation part. (a) to (c) are diagrams showing power trading partners with which power trading is possible centering on EV {v _i }, consumers {d _i }, and PV {pv _i }. It is a flowchart explaining the processing content of a transaction restrictions model preparation part. FIG. 2 illustrates a transmission and distribution network used between EV{v ₁ } and electricity trading; FIG. 2 illustrates a transmission and distribution network used between EV{v ₁ } and electricity trading; FIG. 2 illustrates a transmission and distribution network used between EV{v ₁ } and electricity trading; FIG. 2 illustrates a transmission and distribution network used between EV{v ₁ } and electricity trading;

FIG. 1 is a block diagram showing an example of the configuration of the power trading volume optimization device according to the present embodiment. The power trading volume optimization 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, a RAM and the like. 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, an electricity trading model creation unit 12, a transaction constraint model creation unit 14, an optimization calculation unit 16. An input device 20 and a display device 22 are connected to the power trading volume optimization device 1 shown in FIG. The input device 20 is a user interface for receiving input operations from the user, and is, for example, a mouse or keyboard. The display device 22 is a user interface for displaying information, calculation results, etc. output by the power trading volume optimization device 1, and is, for example, a display.

The storage unit 3 is accessiblely connected to the processing unit 2 and stores an optimization program, an electric vehicle database (hereinafter referred to as EV database 24), a consumer database 26, a photovoltaic power generation device database (hereinafter referred to as PV database 28), and a system database. store 30; Various databases may be stored in a storage device of an external server, for example. In this case, the power trading volume optimization device 1 is connected to the external server via a communication unit such as the Internet, and the processing unit 2 is configured to be able to access the storage device of the external server. .

The EV database 24 includes information on the scheduled parking time and location of the EV, information on the remaining battery level required at the start of EV travel, information on the battery capacity of the EV battery, information on the charging/discharging efficiency of the EV battery, and the like. .

The customer database 26 includes location information of the customer, location information of the charger/discharger owned by the customer, information on the amount of power demanded by 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 flow power in the distribution network, information on the allowable amount of reverse flow power in the power supply network, information on the allowable wheeling amount between the power grids, information on the allowable wheeling amount between the power grids, and information on the allowable wheeling amount between the power grids. It includes power purchase unit price information, power system PV power purchase unit price information, power system power sales unit price information, and transmission charge unit price information between distribution networks.

Information contained 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 containing EVs, consumers, and PVs scattered in a predetermined area. The information that is acquired in advance and included in the system database 30 is information that is received from the system operator of the power transmission and distribution network that is used for power trading between EVs, consumers, and PVs.

Each functional unit of the processing unit 2 will be described below.

The condition setting unit 10 receives input of data on the period and region for which the optimization calculation is to be performed.

FIG. 2 is a flowchart for explaining the processing contents of the power trading model creation unit. The power trading model creation unit 12 refers to the EV database 24, the consumer database 26, the PV database 28, and the system database 30 to obtain customer position information, PV position information, EV parking scheduled time and parking position information. EVs, consumers, and PV included in the period and region (predetermined region) input to the condition setting unit are selected from the above, and from the jurisdictional area information of the power system, the power system related to power trading of EVs, consumers, and PV is selected (step S10).

The power trading model creation unit 12 refers to the consumer database 26, compares the position information of the charger/discharger owned by the selected consumer with the information on the scheduled parking time and parking position of the selected EV, At each time, a charger/discharger connectable to the EV is selected (step S12). For example, a charger/discharger connectable to the EV is selected based on the distance between the position of the charger/discharger and the parking position of the EV.

The power trading model creation unit 12 creates variables (hereinafter referred to as power trading variables) to be obtained by the optimization calculation (step S14). The power trading variable indicates the amount of power trading exchanged among the EV, consumer, PV, and power system selected in step S10. The power trading variables are obtained by enumerating the power trading partners with whom power trading is possible, centering on the selected EV, the selected consumer, and the selected PV. For example, the selected power system is {g ₁ ... g _o }, the selected consumer is {d ₁ ... d _p }, the selected EV is {v ₁ ... v _q }, and the selected PV is For {pv ₁ . . . pv _r }, the following power trading variables are created.

<Electricity trading variables created around EV {v _i }>
FIG. 3(a) is a diagram showing power trading partners with whom power trading is possible centering on EV{v _i }. The power trading partners of EV {v _i } shown in FIG. 3(a) are power system {g _m }, PV {pv _l }, consumer {d _k }, and EV {v _j }. In this case, the amount of power that EV {v _i } purchases from the power system {g _m } at time t: Xg _m v _i (t) (i=1...q, m=1...o), time Amount of power sold by EV {v _i } to electric power system {g _m } at t: Xv _i g _m (t) (i=1...q, m=1...o), EV at time t Amount of electricity {v _i } purchases from PV {pv _l }: Xpv _l v _i (t) (i=1...q, l=1...r), EV{v _i } at time t Amount of electric power sold to consumers {d _k }: Xv _i d _k (t) (i=1...q, k=1...p), EV {v _i } at time t becomes EV {v _j }: Xv _j v _i (t) (i=1...q, j=1...q, i≠j), EV{v _i } at time t becomes EV{v _j }: Xv _{iv j} (t) (i=1...q, j=1...q, i≠j) is the power trading variable.
However, even if the EV is running or parked at time t, if there is no connectable charger/discharger at the parking position, power trading between the EV and the power trading partner is impossible. Therefore, in step S12, the electric power transaction variable is 0 at times other than the time when the connectable charger/discharger is selected for the EV.

<Electricity trading variables created centering on consumers {d _k }>
FIG. 3(b) is a diagram showing power trading partners with whom power trading is possible centering on the consumer {d _k }. Power trading partners of the consumer {d _k } shown in FIG. 3(b) are the electric power system {g _m }, PV {pv _l }, and EV {v _i }. In this case, the amount of power purchased by the consumer {d _k } from the power system {g _m } at time t: Xg _m d _k (t) (k=1...p, m=1...o), Power amount purchased by consumer {d _k } from PV {pv _l } at time t: Xpv _l d _k (t) (k=1 p, l=1 r), demand at time t The amount of power purchased by the house {d _k } from the EV {v _i }: Xv _{id k} (t) (k=1...p, i=1...q) is the power trading variable.
However, as described above, the power trading variable of _{Xvid k (} t) is 0 at times other than the time when the EV connectable charger/discharger is selected in step S12.

<Electricity trading variables created around PV {pv _l }>
FIG. 3(c) is a diagram showing power trading partners with whom power trading is possible centering on PV {pv _l }. The power trading partners of PV {pv _l } shown in FIG. 3(c) are power system {g _m }, EV {v _i }, and consumer {d _k }. In this case, the amount of power sold from the PV {pv _l } to the power grid {g _m } at time t: Xpv _l g _m (t) (l=1...r, m=1...o), Amount of power sold from PV {pv _l } to EV {v _i } at time t: Xpv _l v _i (t) (l=1...r, i=1...q), PV at time t The amount of power sold from {pv _l } to consumers {d _k }: Xpv _l d _k (t) (l=1...r, k=1...p) is a power trading variable.
However, as described above, the power trading variable of Xpv _l v _i (t) is 0 at times other than the time when the EV connectable charger/discharger is selected in step S12.

FIG. 4 is a flow chart for explaining the processing contents of the transaction constraint model creating section. The transaction constraint model creation unit 14 creates constraint conditions that satisfy the power demand of EVs in power transactions involving EVs (FIG. 3(a)) (step S20), and power transactions involving consumers (FIG. 3(b)). Create a constraint condition that satisfies the power demand of the consumer (step S22), create a constraint condition regarding the power generation amount of PV in the power transaction involving PV (Fig. 3(c)) (step S24), EV, consumer , and PV use a power transmission and distribution network in a predetermined area to create constraints on the amount of electricity that can be traded (step S26). Each step will be described below.

<Step S20>
From the EV database 24, the transaction constraint model creation unit 14 obtains information on the remaining battery level required at the start of EV travel (L _vi (t)), information on the battery capacity of the EV (ΔS ^inmax _vi , ΔS ^outmax _vi , S ^max _vi , S ^min _vi ), EV battery charge/discharge efficiency information (η ⁱⁿ _vi , η ^out _vi ), and satisfy the power demand of the EV in the power transaction involving the EV {v _i } in FIG. Create constraints. Specifically, it is represented by the following formulas (1) to (5).

In formulas (1) to (5), S _vi (t): battery charge amount at time t of EV {v _i }, η ⁱⁿ _vi : battery charging efficiency of EV {v _i }, η ^out _vi : EV {v _i } battery discharge efficiency, ΔS ^inmax _vi : EV {v _i } battery chargeable amount per unit time, ΔS ^outmax _vi : EV {v _i } battery dischargeable amount per unit time, S ^max _vi : maximum value of battery charge amount of EV {v _i }, S ^min _vi : minimum value of battery charge amount of EV {v _i }, L _vi (t): EV {v _i } at time t means the power demand (running load) of

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

<Step S22>
The transaction constraint model creation unit 14 acquires information on the electricity demand of the customer from the customer database 26, and satisfies the electricity demand of the customer in the electricity transaction involving the customer {d _k } in FIG. 3(b). Create constraints. Specifically, it is represented by the following formula (6). In the following formula (6), L _dk (t) means the power demand of the consumer {d _k } at time t.

<Step S24>
The transaction constraint model creation unit 14 acquires information on the power generation amount of the selected PV from the PV database 28, and creates a constraint condition on the power generation amount of the PV in the power transaction involving the PV {pv _l } in FIG. 3(c). do. Specifically, it is represented by the following formula (7). In the following formula (7), P _pvl (t) means the power generation amount of PV {pv _l } at time t.

<Step S26>
The transaction constraint model creation unit 14 obtains, from the system database 30, information on the allowable amount of reverse flow power in the distribution network in the predetermined area (DS _n ^out (t)), information on the allowable amount of reverse flow power in the power grid in the predetermined area (TS _gm ^out (t)), information on the allowable transmission volume between power grids (DS _n ⁱⁿ (t)), and information on the allowable transmission volume between power transmission ^grids (TS _gmin (t)) are acquired, and EV, demand Constraint conditions for the amount of power that can be traded are created when a house or PV uses the power transmission and distribution network in a predetermined area to trade power with a power trading partner. Specifically, it is represented by the formulas (8) to (11).

In the following formulas (8) to (11), {TS _gm (gm=1...u)}: transmission network included in the predetermined area, {DS _n (n=1...s)}: in the predetermined area Included distribution networks, ID _dl {TS _dk , DS _dk }: power transmission and distribution networks used by consumers {d _k } during power trading, ID _pvl {TS _pvl , DS _pvl }: PV {pv _l } used during power trading Power transmission and distribution network used, ID _vj (t) {TS _vj (t), DS _vj (t)}: Power transmission and distribution network used at the time of power trading at a position where EV {v _j } can be charged and discharged at time t, TS _gm ^out (t): Allowable power amount flowing out of the power grid TS _gm , TS _gmin (t): ^Allowable power amount flowing into the power grid TS _gm , DS _n ^out (t): Allowable power flowing out of the power distribution network DS _n Quantity, DS _n ⁱⁿ (t): means the amount of power allowed to flow into the distribution network DS _n .

In equations (8)-(11), equation (8) represents a constraint based on the amount of power allowed to flow out of the grid TS _gm , and equation (9) based on the amount of power allowed to flow into the grid TS _gm . Equation (10) represents a constraint based on the amount of power allowed to flow out of distribution network DS _n , and Equation (11) represents a constraint based on the amount of power allowed to flow into distribution network DS _n .

5-8 are diagrams illustrating the transmission and distribution grid used between 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 electric power with consumer {d ₁ } and EV {v ₂ }, equations (8) to The constraint in (11) does not work. Also, for example, as shown in FIG. 6, when EV {v ₁ } uses power distribution network DS ₁ , power transmission network TS ₁ , and power distribution network DS ₂ to trade electric power with consumer {d ₂ }, Since we need to consider DS ₁ ^out (t), DS ₂ ⁱⁿ (t), the constraints of equations (10) and (11) come into play. Also, as shown in FIG. 7, when EV {v ₁ } uses power distribution network DS ₁ and transmission network TS ₁ to trade power with power system g ₁ , DS ₁ ^out (t), TS ₁ ^out Since (t) needs to be considered, the constraints of equations (8) and (10) come into play. Also, as shown in FIG. 8, when EV {v ₁ } uses power distribution network DS ₁ , power transmission networks TS ₁ , TS ₂ , and power distribution network DS ₃ to trade electric power with consumer {d ₃ } Since it is necessary to consider DS ₁ ^out (t), TS ₁ ^out (t), TS ₂ ⁱⁿ (t), and DS ₃ ⁱⁿ (t), the constraints of equations (8) to (11) are works. The above is just an example. For example, if EV {v ₁ } is replaced with PV, it becomes a power transaction between the consumer or EV and PV, and if consumer {d ₂ } is replaced with EV, transmission Power trading is between EVs using the network.

In this way, depending on the power transmission and distribution network used between EVs, consumers, PVs, and power trading partners, different combinations of constraint equations may be applied. Therefore, the transaction constraint model creation unit 14 refers to the system database 30, selects a transmission and distribution network to be used between EVs, consumers, PV and power trading partners from the jurisdictional area information, and selects the selected transmission and distribution network Set a combination of constraint expressions to be acted on based on .

The optimization calculation unit 16 sets maximization of profits in power trading for the entire group including EVs, consumers, and PVs as an objective function based on the created constraint conditions (formulas (1) to (11)). Perform optimization calculations. For example, linear programming, mixed integer programming, non-linear programming, or the like is used for the optimization calculation, but linear programming is preferable in terms of calculation accuracy and the like.

The objective function in the optimization calculation is maximization of the profit (PL) in the power trading of the entire group shown by Equation (12). The profit (PL) in the power trading of the entire group is derived from the power sales income (Income, formula (13)), the purchase cost of grid power (CostP, formula (14)), and the wheeling cost in power trading within the group (CostT , formula (15)) and the incentive to pay to the contractor (CostI, formula (16)). An incentive is a reward paid to a contractor in a group when the contractor makes a power transaction at a specific time.

In formulas (13) to (15), PB _gm (t): power purchase unit price of power system {g _m }, PBPV _gm (t): PV power purchase unit price of power system {g _m }, PS _gm (t) : power sales unit price of power system {g _m }, T _pvlvi (t): transmission charge unit price between PV {pv _l } and EV {v _j }, T _pvldk (t): PV {pv _l } and demand A wheeling charge unit price between house {d _k }, T _vidk (t): Means a wheeling charge unit price between EV {v _j } and customer {d _k }. These unit prices used in formulas (13) to (15) are information contained in the system database 30, and are obtained from the system database 30 when the optimization calculation unit 16 performs the optimization calculation.

In Equation (16), ISv _i g _m : incentive coefficient when EV {v _i } at time t sells power to power grid {g _m }, IBpv _l v _i (t): EV {v _i at time t } purchases from PV {pv _l }, ISv _i d _k (t): incentive coefficient when EV {v _i } sells power to consumer {d _k } at time t, IBv _j v _i (t): incentive coefficient when EV {v _i } purchases from EV {v _j } at time t, IB v _i v _j (t): EV {v _i } to EV {v _j } at time t Incentive coefficient for selling electricity, _IBpv ld _k (t): Incentive coefficient for consumer _{ d _k } to purchase from PV {pv ₁ } at time t, IBv id _k (t): At time t Incentive coefficient when consumer {d _k } purchases from EV {v _i }, ISpv _l g _m (t): incentive coefficient when power is sold from PV {pv _l } to grid {g _m } at time t , ISpv _l v _i (t): incentive coefficient for selling power from PV {pv _l } to EV {v _i } at time t, ISpv _l d _k (t): demand from PV {pv _l } at time t It means an incentive coefficient when selling electricity to a house {d _k }.

Each incentive coefficient is a preset numerical value.

The optimization calculation by the optimization calculation unit 16 calculates the power trading volume (the power trading variable set above) that maximizes the profits from the power trading of the entire group. In this embodiment, the amount of power (Xg _m v _i (t)) purchased by the EV {v _i } from the power system {g _m } and the amount of power sold by the EV {v _i } to the power system {g _m } (Xv _i g _m (t)), EV {v _i } purchases power amount from PV {pv _l } (Xpv _l v _i (t)), EV {v _i } sells to consumer {d _k } electric energy (Xv _i d _k (t)), EV {v _i } purchases electric energy from EV {v _j } (Xv _j v _i (t)), EV {v _i } is EV {v _j }, the amount of power (Xv _i v _j (t)) purchased by the consumer {d _i } from the power system {g _m } (Xg _m d _i (t)), the consumer {d _i } purchased from PV {pv _l } (Xpv _l d _i (t)), consumer {d _i } purchased from EV {v _i } (Xv _j d _i (t)), PV The amount of power sold from {pv _i } to the power system {g _m } (Xpv _i g _m (t)), the amount of power sold from PV {pv _i } to EV {v _j } (Xpv _i v _j ( t)), the power amount (Xpv _i d _k (t)) to be sold from the PV {pv _i } to the consumer {d _k } is calculated.

Further, in the present embodiment, since the power trading volume is calculated for each hour, it is possible to formulate a power trading plan using the power trading volume for each hour.

The power trading volume calculated by the optimization calculation unit, the power trading plan using the power trading, profits calculated using the formulas (12) to (16), and the like are output to the display device 22 .

In this embodiment, the power trading volume is calculated for a group including EVs, consumers, and PVs, but PVs may be excluded from the targets. In this case, the term relating to PV in each equation should be omitted.

Also, in the present embodiment, the power system illustrated as one of the power trading partners with which EVs, consumers, and PVs conduct power trading is an example of the power market.

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

Claims (5)

A power trading volume optimization device for a group including electric vehicles and consumers scattered in a predetermined area,
Constraints satisfying the power demand of the electric vehicle in the power transaction involving the electric vehicle, constraints satisfying the power demand of the consumer in the power transaction involving the consumer, and the electric vehicle and the consumer being in the predetermined area An optimization calculation is performed with an objective function of maximizing profits from power trading for the entire group based on constraints on the amount of power that can be traded with a power trading partner using a power transmission and distribution network, and An electric power trading volume optimization device, wherein the electric vehicle and the consumer in the group calculate the electric power trading volume to be traded with the electric power trading partner. Based on the information about the scheduled parking time and parking position of the electric vehicle and the location information of the customer stored in the storage device, select the electric vehicle and the customer who can conduct power transactions in the group, and 2. The power trading volume optimization device according to claim 1, wherein the power trading volume is calculated for automobiles and consumers. The group includes the electric vehicle and a photovoltaic power generation device that distributes power to the consumer,
3. The method according to claim 1 or 2, wherein the optimization calculation is performed based on the three constraints and a constraint on the amount of power generated by the photovoltaic power generation device in power transactions involving the photovoltaic power generation device. The power trading volume optimization device described. 4. The power trading according to any one of claims 1 to 3, wherein the constraint condition for the power tradeable amount is set based on the allowable power amount information of the power transmission and distribution network stored in the storage device. Quantity optimization device. The power trading volume optimization device according to any one of claims 1 to 4, wherein the optimization calculation uses a linear programming method.

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