Multiple power trading method between consumer and producer under time of use

Abstract

A method for multi-power trading between consumers and producers subject to time-of-use pricing is provided. The simultaneous multi-energy trading method according to an embodiment of the present invention determines power trading strategies representing energy trading volumes based on energy trading prices for each of N consumers subject to time-of-use pricing that constitute a microgrid, searches for energy trading prices within a set range, determines a trading price that maximizes the total revenue of M producers constituting the microgrid based on the power trading strategies of each consumer determined in the first determination step, and processes energy trading between producers and consumers according to the determined trading price. By doing so, the effectiveness of an effective power trading method for multilateral trading in situations where time-of-use pricing is applied can be enhanced.

Description

Technology Field

[0001] The present invention relates to a method for trading electricity, and more specifically, to a method for operating multiple electricity trading in a microgrid composed of M producers and N consumers subject to time-of-use pricing, such that mutual benefits between the electricity supplier and the electricity consumer can be optimized when the M producers trade electricity among the N consumers. Background Technology

[0003] Conventionally, P2P (Peer-to-Peer) bidirectional power trading services between producers and consumers are being operated on various online platforms both domestically and internationally, utilizing diverse trading methods. Most of the trading methods on these existing platforms consist primarily of auction-based bidding or contract-based approaches between producers and consumers.

[0004] However, the bidding or contracting methods of these existing bidirectional power trading operating systems have the following disadvantages: 1) transactions are concluded only between producers and consumers who have been connected through bidding or contracting, while transactions between other producers and consumers are not concluded; 2) most are simple matching forms based on the assumption of a one-to-one situation between producers and consumers; and 3) there is a limitation in that it is not possible to determine whether the proposed quantity and price are optimal by considering the conditions of the trading market and the presenter, as the producer arbitrarily determines the sales volume and sales price, and the consumer arbitrarily determines the energy trading volume and purchase price to participate in the power trading market. The problem to be solved

[0006] The present invention has been devised to solve the aforementioned problems. The objective of the present invention is to provide a method that enables multiple consumers to participate in electricity trading simultaneously and successfully complete multiple transactions, thereby moving away from the restrictive situation where only a single consumer can complete a transaction under existing bidding or contract methods, and allowing multiple consumers to participate in transactions as needed to revitalize the small-scale P2P power trading market between producers and consumers and to enable producers and consumers to participate in the power trading market in a rational manner.

[0007] Furthermore, another objective of the present invention is to provide a method that overcomes the limitations of existing one-to-one transactions between producers and consumers and enables simultaneous M-to-N multiple transactions between any M producers and N consumers.

[0008] Furthermore, another objective of the present invention is to provide a method for enabling rational trading by introducing an optimal power trading decision-making methodology. Unlike existing methods in which producers and consumers determine sales volume and price, energy trading volume and purchase price, and present arbitrary trading quantities and prices to the trading market, this method allows producers and consumers participating in the trading market to determine optimal sales volume and price, energy trading volume and purchase price, and mutual benefits by considering the supply and demand conditions of the trading market and their own circumstances. means of solving the problem

[0010] A method for simultaneous multiple energy trading according to an embodiment of the present invention for achieving the above objective comprises: a first decision step of determining power trading strategies representing energy trading volumes according to energy trading prices for each of N consumers to which a time-of-use pricing system is applied, wherein the energy trading price is searched within a set range, and a second decision step of determining a trading price that maximizes the total revenue of M producers to which the microgrid is composed, based on the power trading strategies of each consumer determined in the first decision step; and a step of processing energy trading between producers and consumers according to the trading price determined in the second decision step.

[0011] The processing step may involve simultaneously processing energy transactions between M producers and N consumers.

[0012] A consumer's electricity trading strategy may be a strategy to derive the optimal energy trading volume for trading prices that are set differently depending on the season and time of day.

[0013] A consumer's power trading strategy may be one in which the consumer's energy trading volume becomes zero when the trading price is equal to the electricity rate at the time of receiving, and the consumer's energy trading volume becomes equal to the consumer's electricity demand when the trading price is zero.

[0014] Consumers' power trading strategies are,

[0015] It is expressed by the following formula,

[0016]

[0017] Here, Q C is the consumer's energy trading volume, D C is the consumer's electricity demand, P MAX is the electricity rate at the time of supply, P is the transaction price, and k can be a constant.

[0018] k can be a constant representing the responsiveness of the energy trading volume according to the trading price.

[0019] In the second decision stage, the energy trading volumes of consumers resulting from fluctuations in energy trading prices may vary based on the power trading strategies of each consumer determined in the first decision stage.

[0020] M producers can conduct transactions by operating generators during time periods that include the peak load hours of the time-based pricing system and some or all of the intermediate load hours.

[0021] The processing step performs energy trading starting with consumers who have a large energy trading volume, and if the producer's supply volume does not meet the energy trading volume during the energy trading with the consumer, the energy trading volume can be set to the producer's current remaining supply volume.

[0022] According to another aspect of the present invention, an energy trading system is provided, comprising: a communication unit connected to communicate with M producers constituting a microgrid and N consumers to whom time-of-use pricing applies; and a processor that determines power trading strategies representing an energy trading volume according to an energy trading price for each consumer, determines a trading price that maximizes the total profit of the producers based on the power trading strategies of each consumer while searching for an energy trading price within a set range, and processes energy trading between the producers and consumers according to the determined trading price.

[0023] According to another aspect of the present invention, a method for simultaneous multiple energy trading is provided, comprising: a first receiving step of receiving information regarding energy supply from M producers constituting a microgrid; a second receiving step of receiving information regarding energy demand from N consumers constituting a microgrid and subject to time-of-use pricing; a first decision step of determining power trading strategies representing energy trading volumes according to energy trading prices for each consumer based on the information received in the second receiving step; a second decision step of determining a trading price that maximizes the total profit of M producers constituting the microgrid based on the power trading strategies for each consumer determined in the first decision step, while searching for energy trading prices within a set range based on the information received in the first receiving step; and a step of processing energy trading between producers and consumers according to the trading price determined in the second decision step.

[0024] According to another aspect of the present invention, an energy trading system is provided, comprising: a communication unit that receives information on energy supply from M producers constituting a microgrid and receives information on energy demand from N consumers constituting the microgrid and subject to time-of-use pricing; and a processor that, based on the information received through the communication unit, determines power trading strategies representing the energy trading volume according to the energy trading price for each consumer, searches for the energy trading price within a set range, determines a trading price that maximizes the total profit of the M producers constituting the microgrid based on the power trading strategies of each consumer, and processes energy trading between the producers and consumers according to the determined trading price. Effects of the invention

[0026] As explained above, according to the embodiments of the present invention, in order to move away from the restrictive situation where only a single consumer can complete a transaction in the bidding or contracting method, which is a P2P power trading method operated on various conventional online platforms, and to enable multiple consumers participating in power trading to participate in transactions simultaneously as needed so that multiple transactions can be completed simultaneously, the participation rate in the small-scale power trading market can be increased and the trading market can be revitalized.

[0027] Furthermore, according to embodiments of the present invention, by applying a method that enables M-to-N multi-power trading between any M producers and N consumers, thereby overcoming the limitations of existing one-to-one trading between producers and consumers, the disadvantages of the existing simple one-to-one matching power trading method are compensated for, and the effectiveness of an effective power trading method for multilateral trading can be enhanced.

[0028] In addition, according to the embodiments of the present invention, unlike the existing method in which producers and consumers determine sales volume and sales price, energy trading volume and purchase price and present arbitrary trading volume and trading price to the trading market, producers and consumers participating in the trading market can determine the optimal sales volume and sales price, energy trading volume and purchase price that optimize mutual benefits by considering the supply and demand situation of the trading market and the situation of the producers and consumers, thereby introducing an optimal power trading decision methodology to enable rational trading, which optimizes the benefits of market participants and secures acceptance among market participants.

[0029] Furthermore, according to embodiments of the present invention, a power trading strategy capable of determining the optimal energy trading volume based on trading prices for off-peak, intermediate, and peak load hours can be extended to the commercial consumer sector for commercial consumers to whom time-of-use pricing is applied. Brief explanation of the drawing

[0031] Fig. 1. Example of a microgrid configuration consisting of M to N producers and consumers Fig. 2. General Electricity (Type A) II Electricity Rate Table (As of Oct. 1, 2022) Fig. 3. Classification by season / time of day (as of Oct. 1, 2022) Fig. 4-6 General Use Electricity (Type A) II High Voltage A Selection I Hourly Electricity Trading Strategy for Consumers in Summer Fig. 7. Load time zone of time-of-use pricing Fig. 8. Change in consumer power trading strategy over time (Example of a transaction between N producers and 1 consumer) Fig. 9. Method for resetting energy trading volume based on consumer's power demand Fig. 10. Multi-power trading method between M-to-N producers and commercial consumers Fig. 11. Changes in energy trading prices by producer over time during the summer Fig. 12. Changes in energy trading prices by producer over time during the winter season Fig. 13. Changes in energy trading revenue by producer Fig. 14. Consumer energy demand and energy trading volume in summer Fig. 15. Consumer energy demand and energy trading volume in winter Fig. 16. Demand, total transaction volume, and revenue of each consumer Fig. 17. Power trading platform for multi-power trading between M-to-N producers and consumers Specific details for implementing the invention

[0032] In an embodiment of the present invention, as a measure to revitalize a small-scale P2P power trading market between producers and consumers and to enable producers (power suppliers) and consumers (power demanders) to participate in the power trading market in a rational manner, a multi-power trading method is proposed that allows multiple consumers participating in power trading to simultaneously participate in transactions as appropriate, thereby enabling multiple transactions to be completed simultaneously, moving away from the restrictive situation where only a single consumer can complete a transaction in existing bidding or contract methods.

[0033] In an embodiment of the present invention, multiple consumers participating in power trading can simultaneously participate in the transaction as appropriate to the situation, thereby enabling multiple transactions to be completed simultaneously. That is, instead of a one-to-one transaction between a producer and a consumer, it enables simultaneous M-to-N multiple transactions between any M producers and N consumers.

[0034] In addition, an embodiment of the present invention presents an optimal power trading decision-making method that allows producers and consumers participating in a trading market to determine the optimal sales volume and sales price, energy trading volume and purchase price, and optimize their profits by considering the supply and demand conditions of the trading market and the circumstances of the producers and consumers.

[0035] The present invention will be described in more detail below with reference to the drawings.

[0036] Figure 1 shows the configuration of a microgrid consisting of a number of (M) producers and a number of (N) consumers to whom time-of-use (TOU) pricing is applied.

[0037] For power trading between producers and consumers in an urban microgrid, a method is required for consumers participating in the power trading market to determine the optimal energy trading quantity based on the market trading price, and in the embodiments of the present invention, this is referred to as a power trading strategy.

[0038] In a multi-power trading method between M producers and N consumers, consumers are assumed to be commercial customers based on time-of-use pricing, and the power trading strategy for determining consumer demand is defined as follows.

[0040] 1. Electricity Trading Strategies for Commercial Consumers

[0041] A large number of commercial customers are defined as consumers, and these consumers are connected to the grid; previously, all electricity could be supplied through power reception.

[0042] In the established power trading strategy, the optimal energy trading volume is derived for the trading price, and the power demand of the corresponding consumers during off-peak, intermediate, and peak hours affects the actual electricity rate.

[0043] Based on the General Electricity (Type A) II electricity rate table for commercial consumers with a contracted power of less than 300kW, the electricity trading strategy of the consumer can be derived as follows.

[0044] Figure 2 is the General Electricity (Type A) II electricity rate table (as of October 1, 2022), and Figure 3 is the classification by season / time of day. Referring to the presented General Electricity (Type A) II High Voltage A Selection I electricity rate table, the consumer's electricity trading strategy regarding quantity-price for the summer season can be graphed as shown in Figures 4 to 6. Figure 4 is the electricity trading strategy during low load, Figure 5 is the electricity trading strategy during medium load, and Figure 6 is the electricity trading strategy during peak load.

[0045] For example, as shown in Fig. 4, if the transaction price between the producer and the consumer during off-peak hours is 70 won, the consumer's energy transaction volume becomes zero because it is the same as the price when receiving power from the grid and there is no need to purchase through trading. Conversely, if the transaction price between the producer and the consumer during off-peak hours is zero and the consumer's power demand during that off-peak hour is D C In this case, the consumer's energy trading volume is the power demand for that time period, D. C You will end up purchasing all of them.

[0046] Therefore, consumers during off-peak hours have a power trading strategy of a linear function as shown in Fig. 4, and similarly, consumers during intermediate and peak hours also have a power trading strategy as shown in Figs. 5 and 6. Assuming the power trading strategies of Figs. 4 to 6 are linear function graphs, and generalizing the equations for trading price and energy trading volume, they can be expressed as the following linear function.

[0047]

[0048] Energy trading volume Q of an arbitrary consumer C is the electricity rate P for the corresponding time period for an arbitrary transaction price P. MAX and electricity demand D C It can be expressed as follows. Here, the transaction price P at light, intermediate, or peak load is the electricity rate (P for the corresponding time period). MAX If it is equal to ), since there is no need to purchase electricity through trading, the energy trading quantity Q in the above equation C becomes zero. Conversely, when the transaction price P at light, intermediate, or peak load is zero, the energy transaction quantity Q C is the power demand D for the corresponding time period C It becomes k times.

[0049] Here, since the maximum benefit from the consumer's perspective is trading the maximum energy volume at the lowest price, k is set as a constant greater than 1; however, if a value less than 1 is set, the energy trading volume Q will remain even if the proposed transaction price is 0. C a Consumer's electricity demand D C This is because it becomes smaller.

[0050] Therefore, the larger the value of k, the greater the responsiveness of the energy trading volume to any transaction price, and the above equation shows that the higher the consumer's electricity rate and the higher the consumer's electricity demand, the greater the energy trading volume can be expected.

[0052] 2. Power Trading Strategy by Load Time for Producer's Time-of-Day Pricing Plan

[0053] Considering the typical scale and characteristics of a producer, their generators are likely to have high variable costs; therefore, to earn a profit above a certain level, the producer must avoid off-peak hours and focus energy trading on peak hours.

[0054] However, due to the characteristics of the generator, it is practically impossible to start the generator only during peak load hours to perform transactions, so it is efficient to operate the generator for a certain continuous period, including intermediate load hours, to perform transactions.

[0055] Figure 7 shows the load time periods of the time-of-use pricing system. As shown, the maximum load periods of the time-of-use pricing system are not continuous, and intermediate load periods are located between the maximum load periods.

[0056] Since it is practically impossible to start the generator only during peak load hours and stop it during other hours for energy trading, and it is also very inefficient in terms of economic feasibility, the producer's energy trading policy is set to enable continuous operation of the generator, including during intermediate load hours, taking into account the relative reduction in profit compared to peak load hours.

[0057] For example, in spring, summer, and autumn, trading is typically performed from 10:00 to 17:00, including the intermediate load period between 12:00 and 13:00 which falls within the peak load period. Unlike other seasons, winter has peak load periods in the evening and at night; therefore, three options are provided to select: a policy to trade from 10:00 to 23:00, including all intermediate load periods; a policy to trade from 10:00 to 12:00 and from 17:00 to 23:00, excluding the relatively long intermediate load period from 12:00 to 17:00; and a policy to trade from 10:00 to 20:00 and from 22:00 to 23:00, which is close to late night hours.

[0059] 3. Power Trading Strategy for Maximizing Producer Profits

[0060] All consumers determine the amount of energy traded according to their set power trading strategy, regardless of the amount of power purchased from other producers at the same time.

[0061] If the amount of electricity purchased by a consumer from another producer at the same time is considered, as illustrated in Fig. 8, when an energy transaction is completed, the producer located later may suffer a disadvantage in revenue due to a relatively smaller amount of energy transaction compared to the same price, as the transaction quantity decreases.

[0062] As shown in Figure 8, in the case of the existing 1-to-N energy trading between one producer and N consumers, if price search is conducted by setting the price determination of one producer and multiple consumers as a separate sequential game, various problems arise in price determination. Therefore, in a multi-power trading environment between any M producers and N consumers, all producers must determine the selling price based on price search for their maximum profit at the same time.

[0063] To determine the sales price of any M producers, the M producers determine the range of price search (Pmin ≤ P ≤ Pmax) by setting the maximum value and the minimum value to an arbitrary value for each load time period of the consumer's time-of-use pricing plan. The price search proceeds from the initial value Pmin to Pmax by increasing in specified minimum price units.

[0064] In other words, to determine the sales price of any M producers, the optimal combination is found by varying the prices of M producers within the price search range (Pmin ≤ P ≤ Pmax), and the energy trading volume of N consumers corresponding to the change in the sales price of M producers is derived through the power trading strategy of commercial consumers derived earlier.

[0065] In this case, the profit of each producer at a specific search price can be expressed as the sum of the products of each selling price proposed by each producer for the search and the different energy trading quantities determined by each consumer's different power trading strategy at the time these selling prices were proposed, as follows.

[0066]

[0067] : Producer k's search price P at a specific transaction time t k Producer's earnings regarding

[0068] : Producer k's search price P at a specific transaction time t k Consumer energy trading volume for

[0069] Therefore, for each of the M producers, by varying the price within the price search range presented above and calculating the profit of each producer at each search price, and by finding the M search prices that maximize the sum of the profits of the M producers, the corresponding M price combinations correspond to the optimal values ​​that the M producers can choose.

[0071] 4. Logic for Resetting Power Trading Volume for Commercial Consumers

[0072] Transactions between each producer and each consumer should be viewed as independent events in which the transaction between a specific producer and consumer does not affect the transaction between other producers and consumers, thereby preventing infinite repetition of price resets caused by interactions between multiple producers and consumers. However, from the perspective of a specific consumer, the amount of energy traded through the commercial consumer power trading strategy is automatically determined according to the optimal price combination obtained by maximizing the profits of M producers, so a situation may arise where the consumer must trade a larger amount of energy with M producers than the demand it requires.

[0073] Therefore, in order to minimize the trading of energy volume exceeding the consumer's power demand from these multiple producers, each consumer must apply an energy trading volume reset logic in which, if the energy trading volume from each producer derived through a consumer power trading strategy based on the optimal price combination of M producers exceeds the power demand, the energy trading volume from each producer is limited to a value equal to the power demand, and if the energy trading volume from each producer is less than the power demand, the energy trading volume from each producer is accepted as is. A flowchart of the corresponding logic is presented in Fig. 9. Fig. 9 is a method for deriving the reset of the energy trading volume based on the consumer's power demand.

[0074] The producer's optimal profit can be derived by multiplying each energy trading volume, changed by the energy trading volume reset logic of each consumer, by the optimal price combination of the M producers calculated above.

[0076] 5. Multi-power trading method between M-to-N producers and commercial consumers

[0077] Figure 10 presents an energy trading method of optimization logic for multi-power trading between M producers and N commercial consumers. Figure 10 is a flowchart provided to explain the multi-power trading method between M producers and N commercial consumers.

[0078] Energy trading takes place in one-hour intervals as the load time zone changes, and the optimization of trading price determination derives the optimal trading price for that one hour.

[0079] In the case of multi-power trading, a trading price that maximizes the producer's total revenue is derived according to the power trading strategy for maximizing the producer's profit mentioned above; when energy trading is performed at the derived trading price, if the energy trading volume exceeds the producer's supply, consumers with higher energy trading volumes are granted priority in energy trading.

[0080] In addition, if the energy trading volume derived from a one-to-one demand function between an arbitrary producer and an arbitrary consumer exceeds the electricity demand of the consumer, the energy trading volume is set to the electricity demand of the consumer, and the specific multi-power trading method is as follows.

[0081] First, collect the producer's energy trading policy for the current time period (S101), and if the energy trading policy is set to perform energy trading in the current time period (S102-YES), proceed with the energy trading process (S103~), otherwise (S102-NO), set the energy trading result to 0 (S106) and terminate the energy trading for the current time period.

[0082] When the energy trading process proceeds, the producer's marginal price, consumer's power demand information, and each consumer's power rate table information are collected (S103, S104, S105). Next, based on the collected information, the optimal energy trading price that maximizes the producer's total profit is derived according to the power trading strategy for maximizing the producer's profit (S107, S108).

[0083] Then, the energy trading volume between one producer and all consumers is derived according to the power trading strategy for each load time period (off-load, intermediate-load, peak-load) of commercial consumers (S109, S110), energy trading is performed starting with consumers with high energy trading volume (S111, S117, S118, S119), and this is repeated for all producers (S120).

[0084] Meanwhile, when performing energy trading between the producer and the consumer as described above, if the producer's supply amount in the current energy trading with the consumer is insufficient to satisfy the energy trading amount (S115-NO), the energy trading amount is set to the producer's current remaining supply amount (S116), and if the producer's supply amount is depleted (S113-NO), the energy trading amount of subsequent consumers in the current time period is set to 0 (S114).

[0086] 6. Computer Simulation

[0087] To verify the validity of the power trading method in a microgrid composed of M-to-N producers and consumers according to an embodiment of the present invention, the following simulation was performed.

[0088] 6.1. Conditions / Progress of Energy Trading Simulation between M-to-N Producers and Consumers

[0089] o Consumers participating in energy trading

[0090] - 54 consumers within a commercial building subject to different or identical general-use electricity rates

[0091] - Power data uses actual measured summer and winter values.

[0092] o Energy trading participating producers

[0093] - Three producers, each with their own energy supply and energy trading policies based on load hours

[0094] - Changes in the producer's energy supply over time are not applied

[0095] - Each has its own unique minimum selling energy price (marginal price), and this price may vary over time based on the producer's energy trading policy.

[0096] - Supply capacity of each producer: 5kW, 5kW, 12kW

[0097] o Progress of the simulation

[0098] - Perform energy trading at 1-hour intervals from 0:00 to 24:00 on the selected date.

[0099] - To maximize producer profits, energy trading does not occur during off-peak hours.

[0100] - Energy trading occurs selectively during intermediate load hours based on the producer's energy trading policy (Summer energy trading hours: 10:00–17:00, Winter energy trading hours: 10:00–23:00)

[0101] - The value representing the responsiveness to price in the consumer demand function is set to 2.

[0103] 6.2. Optimization Simulation Results of Energy Trading Between M-to-N Producers and Consumers Based on Time-of-Day Pricing

[0104] 6.2.1. Changes in Energy Trading Prices According to Load Hours

[0105] o Changes in energy trading prices by producer

[0106] Figures 11 and 12 show the energy trading prices of each producer over time, and reveal changes in energy trading volume due to different energy trading times in summer and winter. It can be confirmed that during the summer energy trading hours, the KEPCO electricity rate decreases only during the intermediate load time slot from 12:00 to 13:00, and consequently, the energy trading price also decreased. When comparing the summer demand graph and the price graph, one might superficially assume that the total hourly demand influences the trading price; however, looking at the winter demand and price graphs between 22:00 and 23:00 confirms that this is not the case.

[0107] In current energy trading algorithms, transactions are conducted with individual consumers rather than across the entire demand; therefore, if there are a few consumers with sufficiently high energy demand, the demand from the majority of consumers with relatively low demand cannot affect the energy trading price. Conversely, if a producer's energy supply increases, active energy trading will take place even with the majority of consumers who have low power demand, so it can be expected that these consumers will influence the energy trading price.

[0108] Ultimately, in the current simulation environment, it can be confirmed that KEPCO electricity rates have a greater impact on energy trading prices than consumer demand.

[0109] o Changes in energy trading revenue by producer are shown in Figure 13.

[0111] 6.2.2. Consumer Energy Demand and Energy Trading Volume

[0112] o Energy trading volume based on consumers' total energy demand

[0113] As shown in Figures 14 and 15, it can be confirmed that the total energy demand of consumers in the summer and winter seasons does not affect the energy trading volume. Even for a consumer with a relatively very large total demand, consumers with smaller demand compared to that consumer actually have a larger energy trading volume.

[0114] o Demand and total transaction volume of each consumer and revenue

[0115] To analyze energy trading in a time-of-use pricing environment, three specific consumers were selected, and the simulation results were compared in Figure 15. It can be seen that Consumer 1 has a large daily energy demand but a small energy trading volume, Consumer 2 has a very large energy trading volume compared to its small demand in winter, and Consumer 3 has a relatively large energy trading volume in both summer and winter with a medium demand scale.

[0117] 7. Multi-power trading platform

[0118] FIG. 17 is a power trading platform for multi-power trading between an M-to-N producer and a consumer according to another embodiment of the present invention. The power trading platform according to an embodiment of the present invention can be implemented as a computing system or server system comprising a communication unit (210), an output unit (220), a processor (230), an input unit (240), and a storage unit (250), as illustrated.

[0119] The communication unit (210) is connected to communicate with M producers constituting the microgrid to receive information on energy supply, and is connected to communicate with N consumers constituting the microgrid to receive information on energy demand.

[0120] The processor (230) performs the simultaneous multiple power trading process shown in FIG. 10 based on information received through the communication unit (210), determines the power trading strategies of consumers, determines a trading price that maximizes the total profit of producers, and processes energy trading between producers and consumers according to the determined trading price.

[0121] The output unit (220) is a display that shows the process and results of simultaneous multiple power trading execution by the processor (230), the input unit (240) is a user interface means that receives user commands and transmits them to the processor (230), and the storage unit (250) provides storage space necessary for the processor (230) to operate and function.

[0123] 8. Variation Example

[0124] So far, a method for simultaneous multiple power trading in a microgrid composed of M producers and N consumers has been described in detail with reference to preferred embodiments.

[0125] In an embodiment of the present invention, an operation method is presented that enables simultaneous multiple power trading to maximize profit for each producer and consumer when M producers trade power with N consumers in a microgrid composed of M producers and N consumers.

[0126] Meanwhile, it goes without saying that the technical concept of the present invention may also be applied to a computer-readable recording medium containing a computer program that enables the device and method according to the present embodiment to perform their functions. Furthermore, the technical concept according to various embodiments of the present invention may be implemented in the form of computer-readable code recorded on a computer-readable recording medium. A computer-readable recording medium may be any data storage device that can be read by a computer and store data. For example, a computer-readable recording medium may be a ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical disk, hard disk drive, etc. Additionally, computer-readable code or a program stored on a computer-readable recording medium may be transmitted through a network connected between computers.

[0127] Furthermore, although preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above. Various modifications are possible by those skilled in the art without departing from the essence of the invention as claimed in the claims, and such modifications should not be understood individually from the technical spirit or perspective of the present invention. Explanation of the symbols

[0129] Producer TOU Consumer

Claims

Claim 1 A first decision step for determining power trading strategies representing energy trading volumes according to energy trading prices for each of N consumers to whom time-of-use pricing applies while configuring a microgrid; a second decision step for determining a trading price that maximizes the total revenue of M producers configuring the microgrid based on the power trading strategies of each consumer determined in the first decision step while searching for energy trading prices within a set range; and a step for processing energy trading between producers and consumers according to the trading price determined in the second decision step; wherein the consumer's power trading strategy is a strategy for deriving energy trading volumes for trading prices that are set differently by season and time of day, expressed by the following formula in which the consumer's energy trading volume becomes zero if the trading price is equal to the electricity rate at the time of receiving, and the consumer's energy trading volume becomes equal to the consumer's electricity demand if the trading price is zero. Here, Q C is the consumer's energy trading volume, D C is the consumer's electricity demand, P MAX A simultaneous multiple energy trading method characterized in that is the electricity rate at the time of receiving, P is the transaction price, and k is a constant. Claim 2 A simultaneous multiple energy trading method according to claim 1, wherein the processing step is characterized by simultaneously processing energy trading between M producers and N consumers. Claim 3 delete Claim 4 delete Claim 5 delete Claim 6 A simultaneous multiple energy trading method according to claim 1, wherein k is a constant representing the responsiveness of the energy trading volume according to the trading price. Claim 7 A simultaneous multiple energy trading method according to claim 1, characterized in that, in the second determination step, the energy trading volumes of consumers according to the fluctuation of energy trading prices are varied based on the power trading strategies of each consumer determined in the first determination step. Claim 8 A simultaneous multiple energy trading method according to claim 1, characterized in that M producers operate generators to perform trading during a time period including the maximum load time of the time-based pricing system and some or all of the intermediate load time periods. Claim 9 A method for simultaneous multiple energy trading according to claim 1, wherein the processing step performs energy trading starting from a consumer with a large energy trading volume, and if the producer's supply volume does not satisfy the energy trading volume in the energy trading with the consumer, sets the energy trading volume to the producer's currently remaining supply volume. Claim 10 A communication unit connected to enable communication with M producers constituting a microgrid and N consumers subject to time-of-use pricing; a processor that determines power trading strategies representing energy trading volumes according to energy trading prices for each consumer, determines a trading price that maximizes the total profit of producers based on the power trading strategies of each consumer while searching for energy trading prices within a set range, and processes energy trading between producers and consumers according to the determined trading price; wherein the consumer's power trading strategy is a strategy for deriving energy trading volumes for trading prices that are set differently by season and time of day, expressed by the following equation in which the consumer's energy trading volume becomes zero if the trading price is equal to the electricity rate at the time of receiving, and the consumer's energy trading volume becomes equal to the consumer's electricity demand if the trading price is zero, and Here, Q C is the consumer's energy trading volume, D C is the consumer's electricity demand, P MAX An energy trading system characterized by the fact that is the electricity rate at the time of receipt, P is the transaction price, and k is a constant. Claim 11 A first receiving step for receiving information on energy supply from M producers constituting a microgrid; a second receiving step for receiving information on energy demand from N consumers constituting a microgrid to which time-of-use pricing applies; a first decision step for determining power trading strategies representing energy trading volumes according to energy trading prices for each consumer based on the information received in the second receiving step; a second decision step for determining a trading price that maximizes the total profit of the M producers constituting the microgrid based on the power trading strategies for each consumer determined in the first decision step, while searching for energy trading prices within a set range based on the information received in the first receiving step. and a step of processing energy transactions between producers and consumers according to the transaction price determined in the second determination stage; wherein the consumer's power trading strategy is a strategy for deriving the energy trading volume for transaction prices that are set differently by season and time of day, expressed by the following formula in which the consumer's energy trading volume becomes zero when the transaction price is equal to the electricity rate at the time of receiving, and the consumer's energy trading volume becomes equal to the consumer's electricity demand when the transaction price is zero, and Here, Q C is the consumer's energy trading volume, D C is the consumer's electricity demand, P MAX A simultaneous multiple energy trading method characterized in that is the electricity rate at the time of receiving, P is the transaction price, and k is a constant. Claim 12 A communication unit that receives information on energy supply from M producers constituting a microgrid and receives information on energy demand from N consumers constituting the microgrid and subject to time-of-use pricing; and a processor that determines power trading strategies representing energy trading volumes according to energy trading prices for each consumer based on information received through the communication unit, determines a trading price that maximizes the total revenue of M producers constituting the microgrid based on the power trading strategies of each consumer while searching for energy trading prices within a set range, and processes energy trading between producers and consumers according to the determined trading price; wherein the consumer's power trading strategy is a strategy for deriving energy trading volume for trading prices that are set differently by season and time of day, expressed by the following equation in which the consumer's energy trading volume becomes zero if the trading price is equal to the electricity rate at the time of receiving, and the consumer's energy trading volume becomes equal to the consumer's electricity demand if the trading price is zero. Here, Q C is the consumer's energy trading volume, D C is the consumer's electricity demand, P MAX An energy trading system characterized by the fact that is the electricity rate at the time of receipt, P is the transaction price, and k is a constant.

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