Electricity trading device, electricity trading method, and program

Abstract

To obtain stable revenue from the charging and discharging operation of energy storage equipment. [Solution] The power trading device of the embodiment is a power trading device that performs continuous trading of buying and selling power products in a predetermined time unit in the power trading market, with power for charging and discharging of energy storage equipment as the trading target, and includes a bidding processing unit that uses already planned operational plan data of the energy storage equipment as initial data, and uses storage capacity range data that shows the range from an upper limit to a lower limit of the amount of energy storage available for continuous trading of the energy storage equipment, and, with the constraint that the amount of energy storage equipment falls within the range shown by the storage capacity range data, selects a power purchase trading product for charging and a power sale trading product for discharging based on bid price data in a continuous trading method and performs continuous trading processing including bidding so as to increase the profit associated with continuous trading.

Description

[Technical Field]

[0001] Embodiments of the present invention relate to a power trading device, a power trading method, and a program. [Background technology]

[0002] With the increasing adoption of power generation facilities utilizing renewable energy sources such as solar power, the need for energy storage is growing to ensure a balance between supply and demand in the power grid. Specifically, energy storage facilities are expected to contribute to load leveling through peak shifting, such as shifting surplus solar power generated during the day to the evening hours when electricity demand increases.

[0003] Furthermore, the domestic wholesale electricity market consists of a spot market (day-ahead market) where transactions are settled using a matching system, and a pre-hour market (same-day market) where transactions are settled through continuous trading (hereinafter simply referred to as "continuous trading"). In the spot market, transactions are settled at equilibrium prices, so generally the bid price and the settlement price do not match, and transactions may not be settled as planned.

[0004] On the other hand, the time-ahead market is a continuous trading market where transactions can be conducted according to market prices up to one hour before the electricity delivery time. The time-ahead market is expected to play a role in compensating for fluctuations in supply and demand plans caused by changes in forecasts of power generation. Furthermore, an increase in trading in the continuous time-ahead market is expected in line with the expansion of power sources using renewable energy.

[0005] Generally, by charging energy storage facilities during periods when demand is low and electricity prices are low relative to power generation, and discharging them during periods when demand is high and electricity prices are high, it is possible to contribute to improving the supply-demand balance. For example, regarding the operation of charging and discharging batteries in accordance with electricity prices, there are known battery control devices that statistically predict trends in electricity prices based on past electricity price trends and select charging and discharging times based on a profit evaluation associated with charging and discharging batteries. [Prior art documents] [Patent Documents]

[0006] [Patent Document 1] Patent No. 6386744 [Overview of the project] [Problems that the invention aims to solve]

[0007] However, electricity prices are affected by daily changes in electricity sales and purchase trends, as well as by weather conditions such as temperature. Therefore, with conventional technology, if electricity price predictions are wrong, the profits from electricity trading and battery charging / discharging may fall significantly lower than expected. In other words, it is difficult to obtain stable profits from the charging and discharging operation of energy storage facilities.

[0008] Therefore, the embodiments of the present invention have been made in view of the above circumstances, and aim to provide a power trading device, a power trading method, and a program that can stably obtain profits from the charging and discharging operation of energy storage equipment. [Means for solving the problem]

[0009] The power trading device of the embodiment is a power trading device that performs continuous trading of buying and selling power products in a power trading market at predetermined time units, with power for charging and discharging of energy storage equipment as the trading target, and includes a bidding processing unit that uses already planned operational plan data of the energy storage equipment as initial data, and uses storage capacity range data that indicates the range from an upper limit to a lower limit of the amount of energy storage available for continuous trading of the energy storage equipment, and, with the constraint that the amount of energy storage equipment falls within the range indicated by the storage capacity range data, selects a power purchase trading product for charging and a power sale trading product for discharging based on bid price data in a continuous trading method and performs continuous trading processing including bidding so as to increase the profits associated with continuous trading. [Brief explanation of the drawing]

[0010] [Figure 1] Figure 1 is a functional configuration diagram of the power trading device according to the first embodiment. [Figure 2]FIG. 2 is an explanatory diagram of the processing content in the first embodiment. [Figure 3] FIG. 3 is a diagram showing a transaction example in the first embodiment. [Figure 4] FIG. 4 is a flowchart showing the processing of bidding method 1 in the first embodiment. [Figure 5] FIG. 5 is a flowchart showing the processing of bidding method 2 in the first embodiment. [Figure 6] FIG. 6 is a graph showing the charge-discharge efficiency characteristics in the first embodiment. [Figure 7] FIG. 7 is a table showing an example of aura value data in the first embodiment. [Figure 8] FIG. 8 is an explanatory diagram of the processing content in the second embodiment.

MODE FOR CARRYING OUT THE INVENTION

[0011] Hereinafter, embodiments (first embodiment, second embodiment) of the power trading device, power trading method, and program of the present invention will be described with reference to the drawings.

[0012] (First Embodiment) FIG. 1 is a functional configuration diagram of the power trading device 1 in the first embodiment. FIG. 2 is an explanatory diagram of the processing content in the first embodiment. FIG. 3 is a diagram showing a transaction example in the first embodiment. The power trading device 1 is a computer device that executes a bulk transaction (for example, a bulk transaction in the time-ahead market 91 (FIG. 2)) of power commodities for each predetermined time unit in the power trading market 9, with the power for charging and discharging a power storage facility (for example, one or more of a storage battery, an electric vehicle, and a pumped-storage power generation facility) as the trading target. Hereinafter, the trading of power commodities will be described by taking the bulk transaction in the time-ahead market 91 as an example. In the time-ahead market 91, power commodities are traded in 30-minute units.

[0013] The power trading device 1 includes, as functional components, a storage unit 2, an input unit 3, a display unit 4, a communication unit 5, and a processing unit 6. In this embodiment, for the sake of simplicity in explanation, the power trading device 1 is described as being constituted by a single computer device, but it is not limited thereto. The power trading device 1 may be realized, for example, by a plurality of computer devices, or part or all of its functions may be realized by a cloud server.

[0014] The storage unit 2 is a means for storing various information, and is realized, for example, by a RAM (Random Access Memory), a ROM (Read Only Memory), a HDD (Hard Disk Drive), an SSD (Solid State Drive), etc. Details of the information stored in the storage unit 2 will be described later.

[0015] The input unit 3 is a means for information input by the user, and is realized, for example, by a mouse, a keyboard, a touch panel, etc.

[0016] The display unit 4 is a means for information display, and is realized, for example, by an LCD (Liquid Crystal Display), etc.

[0017] The communication unit 5 is a communication interface for communicating with an external device.

[0018] The processing unit 6 is a means for performing various arithmetic processes, and is realized, for example, by a CPU (Central Processing Unit). The processing unit 6 includes, as functional components, an acquisition unit 61, a range calculation unit 62, a plan calculation unit 63, a bidding processing unit 64, an optimization calculation unit 65, and a control unit 66.

[0019] The acquisition unit 61 acquires various information from an external device such as the power trading market 9 (the time - ahead market 91).

[0020] The range calculation unit 62 calculates storage capacity range data (for example, 48 intervals every 30 minutes) that shows the range from the upper limit to the lower limit of the amount of energy that can be used for continuous trading in the energy storage equipment, based on various information stored in the storage unit 2, such as the storage capacity range set in advance for the energy storage equipment, information on the use of the energy storage equipment for other purposes, and supply and demand adjustment market transaction data, and stores it in the storage unit 2.

[0021] The planning calculation unit 63 calculates operational planning data (hourly energy storage amount planning data (48 points every 30 minutes)) based on an initial value indicating the starting value in the operational planning data of the energy storage amount of the energy storage equipment (hereinafter also referred to as energy storage amount planning data) (for example, the energy storage amount planning value at 00:00 on the day), a pre-set charge / discharge efficiency characteristic for the energy storage equipment (Figure 6), and already concluded power transaction data, and stores it in the storage unit 2. The planning calculation unit 63 also acquires transaction data when transactions are concluded in the time-ahead market 91 and updates the operational planning data sequentially.

[0022] The bidding processing unit 64 uses the already planned operation plan data for the energy storage facility as initial data, and using the energy storage range data, it uses the constraint that the amount of energy stored in the energy storage facility falls within the range indicated by the energy storage range data. Based on the bid price data using the continuous trading method (bid and ask price data for both bid and ask prices of multiple power products; Figure 7), it uses the latest operation plan data as the initial plan and executes continuous trading processing, including bidding to the pre-hour market 91, by selecting electricity purchase products for charging and electricity sales products for discharging in order to increase the revenue associated with continuous trading.

[0023] Furthermore, the bidding processing unit 64 may use relationship information showing the relationship between pre-set charge / discharge efficiency and load factor to select the number of bids so that the energy storage equipment is operated at a load factor that exceeds a predetermined threshold (threshold TH in Figure 6) for charge / discharge efficiency.

[0024] The optimization calculation unit 65 creates an objective function to maximize the profits associated with continuous trading, and constraints (constraint equations) including the requirement that the amount of energy stored in the energy storage facility falls within the range indicated by the energy storage range data. Based on the objective function and constraints, it uses an optimization algorithm corresponding to integer programming problems to calculate whether there will be bids for each power product, and if so, the number of bids. In that case, the bidding processing unit 64 executes continuous trading based on the calculation results from the optimization calculation unit 65.

[0025] The control unit 66 performs various controls. For example, the control unit 66 performs processing other than that performed by each unit 61 to 65.

[0026] Next, we will explain a specific example of the process. Figure 3 shows the electricity products traded in the advance market 91 (Figure 2) ((c) 48 products with electricity amounts in kWh every 30 minutes) and the energy storage plan ((a)(b)) which calculates the time change in the amount of stored energy due to the charging and discharging operation of the energy storage equipment in accordance with the trading results. The number of the electricity product is i (i=1,...,48), and the energy storage plan after the k-th trade is x. i Let (k)(i=1,…,48).

[0027] The planning calculation unit 63 uses equation (1) to determine the initial value of the energy storage capacity x0 (planned value of the energy storage capacity at 0:00 on the day) and the charging efficiency η c • Discharge efficiency η d Based on the transaction data from the previous day's market trades, hourly energy storage plan data x i (0) is calculated and stored in the storage unit 2. The planning calculation unit 63 further uses equation (2) to obtain the settlement data after the kth trade in the previous time market 91 and stores the energy storage amount plan data x so that the energy storage amount plan always reflects the latest settlement results. i (k) is updated sequentially. Note that q i This indicates the purchase price of commodity i in the previous day's market trading data. Also, r i indicates the electricity sales of commodity i in the previous day's market trading data. W indicates the amount of electricity traded per trading unit.

number

[0028] In addition, the bidding processing unit 64 refers to the bid price data of both the buying intention and selling intention of a plurality of power products in the pre-time market 91, and uses the latest power storage amount plan data as the initial value. Under the constraint that the power storage amount in the power storage facility falls within the range indicated by the power storage possible range data, the optimization calculation unit 65 is used for both additional power purchase bids and selling bids where the trading profit is maximized to calculate the buy bid u i (k), and the sell bid s i (k) (i = 1, …, 48) are calculated at high speed and bid into the pre-time market 91 so as to conclude a bid at the bid price of the target product. Also, by setting the adjustment constant C (set based on the commission fee per trading unit, etc.), the minimum value of the power purchase and selling price difference for calculating the bid can be adjusted.

[0029] The objective function (Equation (3)) and constraint equations (Equations (4) to (6)) are shown below. Here, Xmax indicates the upper limit value of the power storage amount. Xmin indicates the lower limit value of the power storage amount. R i indicates the used portion of the supply and demand adjustment market contract. X end indicates the planned power storage amount value at 24:00 on the same day. u i (k) indicates a buy bid (0: no buy bid. 1: buy bid exists). s i (k) indicates a sell bid (0: no sell bid. 1: sell bid exists). P si (k) indicates the buy bid price. P bi (k) indicates the sell bid price.

Equation

[0030] Figure 4 is a flowchart showing the processing of bidding method 1 in the first embodiment. When the kth transaction is performed in the advance market, as shown in Figure 4, first, the user inputs the number of bid units N, the bid adjustment coefficient C, and the final value of the stored energy Xend (step S1), and the acquisition unit 61 acquires the storage range data and the storage amount plan data from the storage unit 2 (step S2). Here, the number of bid units N is the number of bids relative to the minimum trading unit of the advance market 91 (0.1 MW for 30 minutes = 50 kWh) (minimum trading unit × number of bid units N = amount of electricity traded W), and the number of bids is selected so as not to reduce the efficiency of the energy storage equipment during charging and discharging. Figure 6 shows an example of the characteristics of a power conditioner, and since the charging and discharging efficiency is low in the low load factor region, the number of bids is selected to avoid load factors with low charging and discharging efficiency.

[0031] Next, the acquisition unit 61 acquires the bid price data (order book information) from the pre-hour market 91, and the bidding processing unit 64 selects a bid price according to the number of bid units N (step S3). In the bid price shown in Figure 7, for buy bids, a bid price Psi(k) = 12.4 yen is selected when the number of bid units is 1 to 3, and a bid price Psi(k) = 12.5 yen is selected when the number of bid units is 4 to 8.

[0032] Next, the bidding processing unit 64 creates an objective function and constraints and inputs them to the optimization calculation unit 65 (step S4). Then, the bidding processing unit 64 obtains the calculation results for the number of bids for each product (optimal bid data) from the optimization calculation unit 65, which has performed calculations using the objective function and constraints (step S5).

[0033] Next, in step S6, the bidding processing unit 64 determines whether the total bids for the optimal bid are 1 or more. If yes, it proceeds to step S7; otherwise, it terminates the process.

[0034] In step S7, the bidding processing unit 64 places limit bids in the pre-market 91 with the number of bids N for each product of the optimal bid, the type of electricity purchased / sold, and the respective bid prices.

[0035] Furthermore, if the number of bids in the optimization calculation result is 0 (No in step S6), the energy storage plan cannot be updated to increase transaction revenue, so no bids are made. However, since the market price (bid / ask price data) of electricity products changes moment by moment during trading hours, the result of the bid may change if the bidding processing unit 64 is executed again immediately afterward.

[0036] Furthermore, in order to speed up the process from acquiring bid price data to bidding, the optimization calculation unit 65 may use an optimization solver or pseudo-quantum algorithm capable of solving mixed integer programming problems or 0-1 integer programming problems at high speed.

[0037] Next, we will explain bidding method 2. When the bidding processing unit 64 makes both buy and sell bids, it makes the buy bid first, and then the sell bid after the buy bid is executed. Figure 5 is a flowchart showing the processing of bidding method 2 in the first embodiment. Steps S11 to S15 are the same as steps S1 to S5 in Figure 4.

[0038] After step S15, in step S16, the bidding processing unit 64 determines whether the total of the optimal bids is 1 or more. If yes, proceed to step S18; otherwise, proceed to step S17.

[0039] In step S18, the bidding processing unit 64 places limit bids in the pre-market 91 with the number of buy bids for each product among the best bids and at the bid price.

[0040] Next, in step S19, the bid processing unit 64 determines whether all buy bids have been executed. If yes, it proceeds to step S20; otherwise, it terminates the process.

[0041] In step S20, the bidding processing unit 64 places limit bids in the pre-market 91 with the number of bids and bid price for each product among the best selling bids.

[0042] In step S17, the bidding processing unit 64 determines whether the total of the best selling bids is 1 or more. If yes, it proceeds to step S20; otherwise, it terminates the process.

[0043] Thus, when conducting both buy and sell bids, the electricity purchase agreement should be confirmed before the electricity sale bid is made. This prevents situations where only the electricity sale is agreed upon, resulting in a shortage of delivered power, even if the processing from acquiring the bid price data to bidding is not sufficiently fast.

[0044] Furthermore, bids can be spread out and repeated throughout the trading hours of the advance market 91. For example, if a trading period is expected to have a large price difference between electricity purchase and electricity sale, or a trading period with high trading volume and liquidity, bids may be placed during that trading period.

[0045] Thus, according to the power trading device 1 of the first embodiment, the above-described process makes it possible to stably obtain revenue from the charging and discharging operation of the energy storage facility. In other words, since bidding is performed at high speed so that both electricity purchases and sales are settled without using market price forecast information, it is possible to stably secure revenue from the charging and discharging operation of the energy storage facility without the risk of price forecasts being wrong. Furthermore, it can contribute to load leveling through the operation of the energy storage facility.

[0046] Furthermore, it is possible to execute pre-hourly market transactions that correspond to charge and discharge operations, while taking into account the supply and demand adjustment market and the portion of energy storage equipment used for other purposes.

[0047] Furthermore, since the bidding unit is selected to match the charging and discharging efficiency characteristics of the energy storage equipment, it is possible to execute power transactions that involve operating the energy storage equipment in the range of high charging and discharging efficiency.

[0048] Furthermore, by using bidding method 2, where the seller makes a sell bid only after confirming the completion of the buy bid, it is possible to reduce the risk of having to purchase electricity at a high price or having a shortage of electricity for sale, even if the electricity purchase bid is not completed.

[0049] Furthermore, by selling the unused stored energy after the block in the supply and demand adjustment market has passed, transaction revenue can be increased.

[0050] Furthermore, in the example in Figure 3, bids are possible for 48 products from 17:00 to 23:00 the day before the start of the pre-market 91, and thereafter the number of tradable products decreases every 30 minutes, but bids can be made using the same method. In Figure 3, the first transaction (k1) shows a case where it is possible to increase trading revenue through buying and selling electricity within the range possible in wholesale electricity trading. In other words, symbol T1 represents buying electricity, and symbol T2 represents selling electricity, and as a result, the energy storage plan is changed from symbol G1 to symbol G2.

[0051] Furthermore, in (b), the symbol L1 indicates the lower limit of the stored energy amount from 15:00 to 18:00. The symbol L2 indicates the lower limit of the stored energy amount after 18:00. Then, as shown in the graph of transaction revenue in (c), during the trading hours after the 15:00-18:00 block of the supply and demand adjustment market, the unused stored energy amount is checked and the available storage range data is updated (L1 → L2), and transaction revenue is increased by an additional power sales transaction (the k2nd transaction) (the stored energy plan changes to the symbol G3).

[0052] (Second Embodiment) Next, a second embodiment will be described. For matters similar to those in the first embodiment, redundant explanations will be omitted as appropriate. In the second embodiment, we consider a case where the energy storage system stores electricity generated by a renewable energy generator. In this case, the bidding processing unit 64 also uses information on the electricity generated by the renewable energy generator stored in the energy storage system to perform continuous trading.

[0053] Figure 8 is an explanatory diagram of the processing content in the second embodiment. Here, we will explain a power trading method targeting the time-ahead market or a similar continuous market related to the charging and discharging operation of energy storage facilities that are equipped with renewable energy sources such as solar power generation.

[0054] The planning calculation unit 63 calculates hourly energy storage plan data (48 points every 30 minutes) based on the initial energy storage amount of the energy storage equipment (planned energy storage amount at 0:00 on the day), charging efficiency and discharge efficiency, transaction data from the previous day's market, and renewable energy power generation forecasts (48 points every 30 minutes), and stores it in the storage unit 2. In addition, the planning calculation unit 63 acquires transaction data when transactions are made in the hourly market 91 and updates the operational plan data sequentially.

[0055] The planning unit 63 uses equation (7) (compared to equation (1), the second term on the right-hand side has been added) to calculate hourly energy storage plan data x based on the initial energy storage amount of the energy storage equipment (planned energy storage amount at 0:00), charge / discharge efficiency, and transaction data from the previous day's market trading. i (0) is calculated and stored. Note that Fi represents the predicted renewable energy generation amount. The planning calculation unit 63 further uses equation (8) (same as equation (2)) to calculate the energy storage amount planning data x according to the contract data after the kth trade in the time-ahead market 91. i (k) is updated sequentially.

number

[0056] Furthermore, for the portion of the transaction time during which actual power generation data can be obtained, the accuracy of subsequent optimal bidding can be improved by replacing the power generation forecast with the actual power generation data during calculations.

[0057] In this way, the second embodiment provides the effect of shifting the supply of electricity generated using renewable energy to times of high electricity demand, in addition to the effects of the first embodiment.

[0058] The program executed by the power trading device 1 of this embodiment may be provided as an installable or executable file recorded on a computer-readable recording medium such as a CD-ROM, flexible disk (FD), CD-R, or DVD (Digital Versatile Disk).

[0059] Furthermore, the program may be configured to be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Alternatively, the program may be configured to be provided or distributed via a network such as the Internet.

[0060] Alternatively, the program may be pre-installed and provided in ROM or similar media.

[0061] While several embodiments of the present invention have been described, these embodiments are presented as examples only and are not intended to limit the scope of the invention. These novel embodiments can be carried out in a variety of other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their variations are included in the scope and spirit of the invention, as well as in the claims of the invention and its equivalents.

[0062] For example, in equation (5), the amount of R used in the supply and demand adjustment market contracts i In addition, a section may be added to ensure sufficient storage capacity for purposes such as emergency power supply.

[0063] Furthermore, although the above embodiment shows the case of bidding on kWh products in the advance market, if the market allows bidding on ΔkW products in addition to kWh products, the optimal bid may be calculated using quote data for multiple kWh products and ΔkW products.

[0064] Furthermore, in the second embodiment, the renewable energy power generation equipment is not limited to solar power generation equipment; other equipment, such as wind power generation equipment, may also be used. This would enable power generation even at night. In addition, the portion of the power output using renewable energy may be replaced with a prediction of the inflow into the dam and applied to the operation of a pumped-storage power plant (mixed pumped-storage). [Explanation of symbols]

[0065] 1...Power trading device, 2...Storage unit, 3...Input unit, 4...Display unit, 5...Communication unit, 6...Processing unit, 9...Power trading market, 61...Acquisition unit, 62...Range calculation unit, 63...Plan calculation unit, 64...Bidding processing unit, 65...Optimization calculation unit, 66...Control unit, 91...Hour-ahead market

Claims

1. A power trading device that executes continuous trading of electricity products in a predetermined time unit in the power trading market, with electricity for charging and discharging energy storage equipment as the trading object, A power trading device comprising: an auction processing unit that uses already planned operational plan data for the energy storage facility as initial data, and uses energy storage range data indicating the range from the upper limit to the lower limit of the amount of energy storage available for continuous trading in the energy storage facility, and, with the constraint that the amount of energy storage in the energy storage facility falls within the range indicated by the energy storage range data, selects a power purchase trading product for charging and a power sale trading product for discharging based on bid price data using a continuous trading method, and executes continuous trading processing including bidding, so as to increase the profits associated with continuous trading.

2. The power trading device according to claim 1, further comprising a range calculation unit that calculates the energy storage range data based on a preset energy storage range for the energy storage equipment and information on the use of the energy storage equipment for other purposes.

3. The power trading device according to claim 1, further comprising a planning calculation unit that calculates the operation plan data based on an initial value indicating the starting value of the amount of energy stored in the energy storage equipment in the operation plan data, a preset charge / discharge efficiency characteristic for the energy storage equipment, and power trading data that has already been agreed upon.

4. An objective function is created to maximize the profits associated with continuous trading, and constraints are created including the requirement that the amount of energy stored in the energy storage facility falls within the range indicated by the energy storage range data. The system further includes an optimization calculation unit that, based on the objective function and constraints, uses an optimization algorithm corresponding to an integer programming problem to calculate whether or not there is a bid for each power product, and if so, the number of bids. The electricity trading apparatus according to claim 1, wherein the bidding processing unit executes the continuous trading process based on the calculation results of the optimization calculation unit.

5. The power trading device according to claim 1, wherein the bidding processing unit uses relationship information showing the relationship between pre-set charge / discharge efficiency and load factor to select the number of bids so that the energy storage equipment is operated at a load factor that exceeds a predetermined threshold for charge / discharge efficiency.

6. The electricity trading apparatus according to claim 1, wherein, when the bidding processing unit conducts both buy and sell bids, it conducts buy bids first and then sells bids after the buy bids have been agreed upon.

7. The power trading device according to claim 1, wherein the energy storage equipment is at least one of a battery storage system, an electric vehicle, or a pumped-storage hydroelectric power plant.

8. The aforementioned energy storage equipment stores electricity generated by renewable energy generators, The electricity trading apparatus according to claim 1, wherein the bidding processing unit also uses information on the electricity generated by the renewable energy generator stored in the energy storage facility to perform the continuous trading process.

9. A method of trading electricity using an electricity trading device that executes continuous trading of electricity products in predetermined time units in the electricity trading market, with electricity for charging and discharging energy storage equipment as the trading subject, A power trading method comprising a bidding processing step in which a bidding processing unit uses already planned operational plan data for the energy storage facility as initial data, and uses energy storage range data indicating the range from an upper limit to a lower limit of the amount of energy storage available for continuous trading in the energy storage facility, and, with the constraint that the amount of energy storage in the energy storage facility falls within the range indicated by the energy storage range data, selects a power purchase trading product for charging and a power sale trading product for discharging based on bid price data using a continuous trading method, and executes continuous trading processing including bidding, so as to increase the profits associated with continuous trading.

10. A computer that is a power trading device that executes continuous trading of electricity products in the power trading market at predetermined time intervals, with electricity for charging and discharging energy storage equipment as the trading subject, A program to function as a bidding processing unit that uses already planned operational plan data for the aforementioned energy storage facility as initial data, and uses energy storage range data indicating the range from the upper limit to the lower limit of the amount of energy storage available for continuous trading in the aforementioned energy storage facility, with the constraint that the amount of energy storage in the aforementioned energy storage facility falls within the range indicated by the energy storage range data, and based on bid price data using a continuous trading method, selects a power purchase trading product for charging and a power sale trading product for discharging in order to increase the profits associated with continuous trading, and executes continuous trading processing including bidding.

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