A multi-region sharing based energy game regulation method and device

Abstract

The application discloses a kind of energy game regulation and control method and equipment based on multi-region sharing.The method comprises the following steps: constructing energy sharing subject model, including the power consumption comprehensive benefit model of producer and consumer and the income model of energy operator;Energy operator obtains scheduling result with maximum income as objective function;Producer and consumer pursue greater income effect according to the regional internal electricity price provided by energy operator;Energy operator pursues smaller operation cost according to the scheduling result of shared energy storage system;If the game decision result of producer and consumer and energy operator does not change, the transaction result is taken as the final energy transaction regulation scheme, otherwise return to continue iteration.The application provides a technical scheme for power system operation management under the background of the vigorous development of new energy and shared energy storage, enhances inter-regional energy sharing and promotes renewable energy consumption.

Description

Technical Field

[0001] This invention relates to the field of power system operation control, and specifically to a method and device for energy game regulation based on multi-region sharing. Background Technology

[0002] Developing renewable energy and achieving a cleaner and lower-carbon energy structure has become a consensus in social development. However, with the rapid development of renewable energy, which is characterized by intermittency and randomness, the power grid is facing unprecedented pressure to absorb new energy.

[0003] Currently, both domestically and internationally, to optimize the absorption of fluctuations in renewable energy output on the user side, methods such as configuring energy storage systems and demand response are mainly adopted. This aims to promote energy sharing and absorption within the region as much as possible, reducing the impact of peak-valley load fluctuations on the upper-level power grid. Although energy storage has great application prospects, its promotion and popularization on the user side are hindered by factors such as high investment costs and long payback periods. Shared energy storage can share the construction and maintenance costs among users, improving energy storage utilization efficiency and operational benefits. Simultaneously, with the rapid deployment of distributed photovoltaics, a large number of photovoltaic power generation devices are installed in many community buildings, thereby saving electricity costs. Under the background of demand-side trading reform in the electricity market, the energy status of community building clusters within a certain area can be integrated into a single entity, participating in the demand response process based on current market electricity prices and their own net load.

[0004] To balance the interests of all parties involved in the transaction process, game theory can be introduced to quantify and study such problems. Existing game theory studies on energy sharing, such as the paper "Optimization of Distributed Photovoltaic and Shared Energy Storage Capacity in Producer-Seller Communities Based on Cooperative Game Theory," mostly consider only the game between a single operator and multiple users. Operators are prone to exploiting their market advantage to maliciously raise electricity prices in pursuit of greater profits. Meanwhile, user entities often only consider the distribution of benefits through cooperative alliances using methods such as the Shapley value method. However, users' marginal contributions often involve the privacy of their specific electricity consumption benefits, making it difficult to collect and reflect the true situation, and thus failing to solve energy sharing optimization problems that are more closely aligned with real-world scenarios. In real-world scenarios, different energy-consuming areas have different load characteristics, and the configuration and scheduling optimization of shared energy storage need to be adjusted to match the regional load characteristics. Furthermore, to better pursue the economic benefits brought by demand response, operators should also adjust the time-of-use pricing optimization for different regions according to their load characteristics. Summary of the Invention

[0005] Therefore, in view of the above problems, the purpose of this invention is to solve the scheduling problem of energy sharing in a multi-regional environment, so as to meet the regional electricity demand, improve the economic benefits of producers and consumers and energy operators, and absorb new energy sources as much as possible.

[0006] The objective of this invention is achieved by at least one of the following technical solutions.

[0007] A multi-region shared energy game-theoretic control method includes the following steps:

[0008] S1. Initialize producer-consumer and energy operator information, divide into N trading zones according to net load, and determine the purchase and sale volume of different zones; the trading zone is the area under the jurisdiction of the energy operator in which producer-consumers can choose to buy or sell electricity; the purchase volume is the total demand of all producer-consumers in the same zone; the sale volume is the total surplus of all producer-consumers in the same zone.

[0009] S2. Construct an energy-sharing entity model, including a comprehensive electricity consumption benefit model for producers and consumers and a revenue model for energy operators;

[0010] S3. Based on the electricity purchase and sale information submitted by producers and consumers, the energy operator uses the maximization of revenue as the objective function and calculates the scheduling results to obtain the electricity value within the region, the scheduling results of the shared energy storage system, and the energy sharing value within and between regions.

[0011] S4. Producers and consumers can pursue greater profitability by modifying their purchased and sold electricity volumes and selecting trading regions based on the regional electricity prices provided by energy operators; energy operators can redetermine the configuration capacity of shared energy storage based on the scheduling results of the shared energy storage system, in order to pursue lower operating costs.

[0012] S5. If the game decision-making results of producers and consumers and energy operators do not change, then the transaction result shall be used as the final energy transaction regulation plan; otherwise, return to step S3 and continue to repeat the iteration.

[0013] Furthermore, in step S2, for producers and consumers, a comprehensive electricity consumption benefit model is constructed based on their interest characteristics, and their electricity purchase and sale volume and transaction area variables are initialized; for energy operators, a revenue model is constructed based on their interest characteristics, and the internal electricity price, energy storage capacity, and energy storage power within their jurisdiction are initialized.

[0014] Furthermore, the comprehensive electricity consumption benefit model for any producer-consumer includes: an electricity consumption benefit component and an electricity trading benefit component, as detailed below:

[0015] The electricity efficiency component is as follows:

[0016]

[0017] in, It is the electricity consumption benefit of producer-consumer i in region n and time t; It is the actual electricity consumption of producer-consumer i in region n and time t; It is the efficiency coefficient of producer-consumer i in region n and time t. The higher the value, the more actively the producer-consumer consumes electricity to obtain greater benefits.

[0018] The benefits of constructing an electricity trading system include:

[0019]

[0020] in, It is the profit from selling electricity or the expenditure on electricity by producer-consumer i during the transaction process in region n and time t. These represent the electricity purchase price and the electricity sales price for producer-consumer i when purchasing electricity from the operator in region n and time t, respectively. This indicates whether consumer i chooses to trade in region n within time t. This indicates that the user has selected this area for trading, otherwise it indicates...

[0021] Furthermore, the revenue models for energy operators include: the electricity dispatch revenue model and the shared energy storage system model;

[0022] The power dispatch benefit model is as follows:

[0023]

[0024] Among them, R opr This refers to the operator's operating revenue within region n and time t. These represent the electricity purchase quota and electricity sales quota for users within region n during time period t, respectively; γ mid The toll payable to the power grid when electricity is transmitted through medium and low voltage distribution networks;

[0025] The shared energy storage system model is as follows:

[0026]

[0027]

[0028]

[0029] in, Let represent the energy storage state of the shared energy storage system in region n within time t+1; The energy storage status of the shared energy storage system in region n within time t; This represents the maximum capacity of the shared energy storage system. The charging and discharging power of the shared energy storage system within time t; This represents the maximum charging and discharging power of the shared energy storage system. This indicates that the shared energy storage system in region n is charging within time t. This indicates that the shared energy storage system in region n discharges within time t. This indicates that the shared energy storage system in region n does not charge or discharge within time t.

[0030] Furthermore, in step S3, based on the electricity purchase and sale information, the comprehensive electricity consumption benefit model of producers and consumers, and the revenue model of energy operators, the optimal electricity consumption is obtained by taking the first derivative of the revenue function of producers and consumers with respect to electricity consumption and making it equal to zero. This is then input into the revenue function of energy operators, and the electricity value within the region, the capacity and charge / discharge status value of the shared energy storage system, and the energy sharing value between regions are calculated.

[0031] When the total electricity sales of producers and consumers in a region exceed the total electricity purchases, the region as a whole is in a state of surplus electricity. The energy dispatching process of the energy operator is as follows:

[0032] First, the surplus electricity currently sold by producers and consumers will be prioritized and dispatched to producers and consumers who currently need to purchase the shortfall in electricity to meet their electricity demand.

[0033] Secondly, the remaining electricity will be allocated in two ways depending on the situation: First, if the current electricity price in the region is high and other regions have a demand for electricity, the electricity can be sold to other regions; second, the electricity can be stored in a shared energy storage system to prepare for the system to discharge during periods of power shortage; if there is still remaining electricity at this time, the remaining electricity will be fed into the grid.

[0034] When the total electricity sales of producers and consumers within a region are less than the total electricity purchases, the region as a whole is in a state of power shortage. The power dispatching process of the energy operator is as follows:

[0035] First, the surplus electricity currently sold by producers and consumers will be prioritized and dispatched to producers and consumers who currently need to purchase the shortfall in electricity to meet their electricity demand.

[0036] Secondly, there are two dispatching schemes for the shortfall in electricity: one is to purchase electricity from other regions when the purchase price of electricity in other regions is lower than that of the grid, and when other regions have surplus electricity, as much electricity as possible can be purchased from them; the other is to share the energy storage system to discharge electricity to meet the demand. If there is still a shortfall in electricity at this time, electricity will be purchased from the grid to make up for the demand.

[0037] Furthermore, the following constraints should be met during the power dispatching process of energy operators:

[0038] Power balance constraints in each region:

[0039]

[0040] Electricity price constraints within each region:

[0041]

[0042] n={1,2,…,N},t={1,2,…,24}

[0043] in, Let be the interaction power between region n and the power grid within time t; The energy input and output power between different regions within time t; These represent the electricity purchase price and the electricity sales price of producer-consumer i when purchasing electricity from the grid in region n and time t, respectively.

[0044] Furthermore, in step S4, both producers and consumers, as well as energy operators, can modify their own parameters based on the scheduling results to pursue better efficiency; the specific steps are as follows:

[0045] S4.1 Producers and consumers may reselect a trading area that provides better overall electricity consumption benefits and adjust their own electricity consumption. The process of selecting a trading area and adjusting electricity consumption should meet the following constraints:

[0046]

[0047]

[0048] in, Let these represent the minimum and maximum electricity consumption of producer-consumer i in region n and time t, respectively.

[0049] S4.2. Based on the scheduling results in step S3, the energy operator can redetermine the shared energy storage configuration capacity. The energy operator's revenue model takes maximizing power dispatch revenue and minimizing operating and investment costs as its objective function, specifically:

[0050]

[0051]

[0052]

[0053] Among them, R trans The operating costs for energy operators when optimizing energy allocation across all regions; γ high This refers to the toll paid to the high-voltage power grid when electricity is transmitted. When the demand for electricity in region n exceeds the supply, the amount of electricity transmitted through the high-voltage grid equals the amount received from other regions, and vice versa. C stoC represents the investment cost required by energy operators for energy storage equipment in the region. inv,n C represents the annualized investment cost per unit capacity of energy storage equipment in region n; main,n Let r be the unit power energy storage equipment cost in region n; r be the discount rate; l n Let n be the operating life of the energy storage devices in region n.

[0054] Furthermore, in step S5, based on the recalculated producer-consumer selection results and energy storage capacity configuration results, it is determined whether the decision result has changed compared with the previous comparison; if the decision result has changed, the process returns to step S3 to continue iterative calculation until the decision result no longer changes; if the decision result is the same, the decision result of this transaction is taken as the final energy trading control scheme.

[0055] A game-theoretic control device based on multi-regional energy sharing, comprising:

[0056] The determination unit is used to determine the information of producers and consumers participating in regional energy sharing, including their selected trading area variables and actual electricity consumption; and to determine the information of energy operators participating in regional energy sharing, including their set intra-regional electricity price, energy storage charging and discharging status value, and inter-regional energy sharing value.

[0057] The unit is used to establish a comprehensive electricity consumption benefit model for producers and consumers and a revenue model for energy operators based on information from producers and consumers and energy operators. It can also transform the relevant parameters by taking derivatives, and finally establish a multi-regional energy sharing game model with the objective function of maximizing the revenue of energy operators and minimizing operating and investment costs.

[0058] The solution unit is used to solve the multi-region energy sharing game model, determine whether the game iteration has ended, and finally obtain the optimal parameter configuration of the multi-region energy sharing game model so that producers and consumers and energy operators can carry out energy trading regulation based on the obtained optimal parameters.

[0059] Compared with the prior art, the advantages of the present invention are as follows:

[0060] The proposed energy game regulation method based on multi-regional sharing provided by this invention has the following significant effects: it optimizes the energy sharing and utilization among multiple regions, thereby improving the overall electricity consumption benefits for users in each region, increasing the operating income of energy operators, and enhancing the system's ability to absorb new energy sources. The resulting scheduling method is more in line with reality. Attached Figure Description

[0061] Figure 1 This is a schematic diagram illustrating the steps of a multi-regional energy game-based regulation method.

[0062] Figure 2A comparison chart of scheduling results status;

[0063] Figure 3 A comparison chart of producer and consumer benefits;

[0064] Figure 4 This is a comparison chart of the revenue of energy operators in Embodiment 1 of the present invention;

[0065] Figure 5 This is a comparison chart of the net system load in Embodiment 1 of the present invention;

[0066] Figure 6 This is a diagram of the net producer-consumer load in Embodiment 1 of the present invention;

[0067] Figure 7 This is a comparison chart of the revenue of energy operators in Embodiment 2 of the present invention;

[0068] Figure 8 This is a comparison chart of the net system load in Embodiment 2 of the present invention;

[0069] Figure 9 This is a diagram of the producer-consumer net load status in Embodiment 2 of the present invention;

[0070] Figure 10 This is a comparison chart of the revenue of energy operators in Embodiment 3 of the present invention;

[0071] Figure 11 This is a comparison chart of the net system load in Embodiment 3 of the present invention;

[0072] Figure 12 This is a diagram showing the net load of producers and consumers in Embodiment 3 of the present invention. Detailed Implementation

[0073] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings and examples. It is obvious that the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments of the present invention obtained by those skilled in the art based on the embodiments of the present invention without inventive effort, and all other embodiments obtained by those skilled in the art without inventive effort, are within the scope of protection of the present invention.

[0074] Example:

[0075] A multi-region shared energy game-based regulation method, such as Figure 1 As shown, it includes the following steps:

[0076] S1. Initialize producer-consumer and energy operator information, divide into N trading zones according to net load, and determine the purchase and sale volume of different zones; the trading zone is the area under the jurisdiction of the energy operator in which producer-consumers can choose to buy or sell electricity; the purchase volume is the total demand of all producer-consumers in the same zone; the sale volume is the total surplus of all producer-consumers in the same zone.

[0077] S2. Construct an energy-sharing entity model, including a comprehensive electricity consumption benefit model for producers and consumers and a revenue model for energy operators;

[0078] For producers and consumers, a comprehensive electricity consumption benefit model is constructed based on their interest characteristics, and their electricity purchase and sale volume and transaction area variables are initialized; for energy operators, a revenue model is constructed based on their interest characteristics, and the internal electricity price, energy storage capacity, and energy storage power within their jurisdiction are initialized.

[0079] The comprehensive electricity consumption benefit model for any producer-consumer includes: an electricity consumption benefit component and an electricity trading benefit component, as detailed below:

[0080] The electricity efficiency component is as follows:

[0081]

[0082] in, It is the electricity consumption benefit of producer-consumer i in region n and time t; It is the actual electricity consumption of producer-consumer i in region n and time t; It is the efficiency coefficient of producer-consumer i in region n and time t. The higher the value, the more actively the producer-consumer consumes electricity to obtain greater benefits.

[0083] The benefits of constructing an electricity trading system include:

[0084]

[0085] in, It is the profit from selling electricity or the expenditure on electricity by producer-consumer i during the transaction process in region n and time t. These represent the electricity purchase price and the electricity sales price for producer-consumer i when purchasing electricity from the operator in region n and time t, respectively. This indicates whether consumer i chooses to trade in region n within time t. This indicates that the user has selected this area for trading, otherwise it indicates...

[0086] The regional operation model of the energy operator includes: a power dispatch revenue model and a shared energy storage system model;

[0087] The power dispatch benefit model is as follows:

[0088]

[0089] Among them, R opr This refers to the operator's operating revenue within region n and time t. These represent the electricity purchase quota and electricity sales quota for users within region n during time period t, respectively; γ mid The toll payable to the power grid when electricity is transmitted through medium and low voltage distribution networks;

[0090] The shared energy storage system model is as follows:

[0091]

[0092]

[0093]

[0094] in, Let represent the energy storage state of the shared energy storage system in region n within time t+1; The energy storage status of the shared energy storage system in region n within time t; This represents the maximum capacity of the shared energy storage system. The charging and discharging power of the shared energy storage system within time t; This represents the maximum charging and discharging power of the shared energy storage system. This indicates that the shared energy storage system in region n is charging within time t. This indicates that the shared energy storage system in region n discharges within time t. This indicates that the shared energy storage system in region n does not charge or discharge within time t.

[0095] S3. Based on the electricity purchase and sale information submitted by producers and consumers, the energy operator uses the maximization of revenue as the objective function and calculates the scheduling results to obtain the electricity value within the region, the scheduling results of the shared energy storage system, and the energy sharing value within and between regions.

[0096] Based on the electricity purchase and sale information, the comprehensive electricity consumption benefit model of producers and consumers, and the revenue model of energy operators, the optimal electricity consumption is obtained by taking the first derivative of the revenue function of producers and consumers with respect to electricity consumption and setting it to zero. This optimal electricity consumption is then substituted into the revenue function of energy operators, and the electricity value within the region, the capacity and charge / discharge status of the shared energy storage system, and the energy sharing value between regions are calculated.

[0097] When the total electricity sales of producers and consumers in a region exceed the total electricity purchases, the region as a whole is in a state of surplus electricity. The energy dispatching process of the energy operator is as follows:

[0098] First, the surplus electricity currently sold by producers and consumers will be prioritized and dispatched to producers and consumers who currently need to purchase the shortfall in electricity to meet their electricity demand.

[0099] Secondly, the remaining electricity will be allocated in two ways depending on the situation: First, if the current electricity price in the region is high and other regions have a demand for electricity, the electricity can be sold to other regions; second, the electricity can be stored in a shared energy storage system to prepare for the system to discharge during periods of power shortage; if there is still remaining electricity at this time, the remaining electricity will be fed into the grid.

[0100] When the total electricity sales of producers and consumers within a region are less than the total electricity purchases, the region as a whole is in a state of power shortage. The power dispatching process of the energy operator is as follows:

[0101] First, the surplus electricity currently sold by producers and consumers will be prioritized and dispatched to producers and consumers who currently need to purchase the shortfall in electricity to meet their electricity demand.

[0102] Secondly, there are two dispatching schemes for the shortfall in electricity: one is that when the purchase price of electricity in other regions is lower than that of the grid, and other regions have surplus electricity, electricity can be purchased from them as much as possible; the other is that the shared energy storage system can discharge to meet the electricity demand; if there is still a shortfall in electricity at this time, electricity will be purchased from the grid to make up for the electricity demand.

[0103] The following constraints should be met during the power dispatching process of energy operators:

[0104] Power balance constraints in each region:

[0105]

[0106] Electricity price constraints within each region:

[0107]

[0108] n={1,2,…,N},t={1,2,…,24}

[0109] in, Let n be the power transmitted by the grid to region n within time t. The energy input and output power between regions within time t; These represent the electricity purchase price and the electricity sales price of producer-consumer i when purchasing electricity from the grid in region n and time t, respectively.

[0110] S4. Producers and consumers can pursue greater profitability by modifying their purchased and sold electricity volumes and selecting trading regions based on the regional electricity prices provided by energy operators; energy operators can redetermine the configuration capacity of shared energy storage based on the scheduling results of the shared energy storage system, in order to pursue lower operating costs.

[0111] Both producers and consumers, as well as energy operators, can modify their own parameters based on the scheduling results to pursue better efficiency; the specific steps are as follows:

[0112] S4.1 Producers and consumers may reselect a trading area that provides better overall electricity consumption benefits and adjust their own electricity consumption; the process of selecting a trading area and adjusting electricity consumption should meet the following constraints:

[0113]

[0114]

[0115] in, Let these represent the minimum and maximum electricity consumption of producer-consumer i in region n and time t, respectively.

[0116] S4.2 Based on the aforementioned scheduling results, the energy operator can redetermine the shared energy storage configuration capacity. The energy operator's revenue model takes maximizing power dispatch revenue and minimizing operating and investment costs as its objective function, specifically:

[0117]

[0118]

[0119]

[0120] Among them, R trans The operating costs for energy operators when optimizing energy allocation across all regions; γ high This refers to the toll paid to the high-voltage power grid when electricity is transmitted. When the demand for electricity in region n exceeds the supply, the amount of electricity transmitted through the high-voltage grid equals the amount received from other regions, and vice versa. C sto C represents the investment cost required by energy operators for energy storage equipment in the region. inv,n C represents the annualized investment cost per unit capacity of energy storage equipment in region n; main,n Let r be the unit power energy storage equipment cost in region n; r be the discount rate; l n Let n be the operating life of the energy storage devices in region n.

[0121] S5. If the game decision results between the producers and consumers and the energy operators do not change, then the transaction result shall be taken as the final energy transaction regulation scheme; otherwise, return to step S3 and continue to repeat the iteration.

[0122] Based on the recalculated producer-consumer selection results and energy storage capacity configuration results, determine whether the decision result has changed compared with the previous comparison; if the decision result has changed, iterative calculation should continue until the decision result no longer changes; if the decision result is the same, the decision result of this transaction shall be used as the final energy trading control scheme.

[0123] A game-theoretic control device based on multi-regional energy sharing, the device comprising:

[0124] The determination unit is used to determine the information of producers and consumers participating in regional energy sharing, including their selected trading area variables and actual electricity consumption; and to determine the information of energy operators participating in regional energy sharing, including their set internal regional electricity price, energy storage charging and discharging status value, and inter-regional energy sharing value.

[0125] The unit is used to establish a comprehensive electricity consumption benefit model for producers and consumers, a revenue model for energy operators, and a cost model for energy operators based on information from producers and consumers and energy operators. It can also transform the relevant parameters by taking derivatives, and finally establish a multi-regional energy sharing game model with the objective functions of maximizing the revenue and minimizing the cost of energy operators.

[0126] The solving unit is used to solve the game model based on multi-regional energy sharing, determine whether the game iteration has ended, and finally obtain the optimal parameter configuration of the multi-regional energy sharing game model so that producers and consumers and energy operators can carry out energy trading regulation according to the optimal configuration parameters.

[0127] In this embodiment, in order to verify the effectiveness of the method proposed in this invention, a simulation analysis is conducted using a building cluster user in a southern province as an example.

[0128] Among them, the photovoltaic output and load levels of users in each building cluster are as follows: Figure 2 As shown in the diagram. Assume users 1, 2, and 3 are originally connected to the power grid in region 1, users 4 and 5 to region 2, and users 6 and 7 to region 3. Users can reconnect their lines to different neighboring power grids by adjusting the low-voltage side switch. Users 1 to 3 can choose regions 1 and 2, and users 4 to 7 can choose regions 2 and 3. The net load levels for each user are shown in the appendix. The grid access fee for 10kV lines is 0.015 yuan / kWh, and the grid access fee for 110kV lines is 0.01 yuan / kWh. The unit capacity investment cost of equipping energy storage devices in each region is 1500 yuan / kWh, the unit power investment cost is 300 yuan / kWh, the operating life is 10 years, and the discount rate is 4.9%. To better illustrate the superiority of the proposed scheme, the following three scenarios will be analyzed and compared:

[0129] Scenario 1: Users trade with energy operators based on grid electricity prices and independently utilize energy storage for optimized scheduling;

[0130] Scenario 2: Based on cooperative game theory, users form alliances to achieve energy sharing between and within regions. They also participate in optimized scheduling by utilizing energy storage systems and adjusting their own loads according to the electricity prices set by the operator, and ultimately distribute benefits through the Shapley value method.

[0131] Scenario 3: The multi-regional energy sharing optimization strategy proposed in this invention is based on master-slave game theory. The energy operator acts as the leader, sets differentiated electricity prices for different trading regions, and completes energy optimization scheduling including energy storage. Users act as followers, selecting trading regions and adjusting their own loads according to inter-regional electricity prices.

[0132] Based on steps S1 to S5, the optimized scheduling results obtained under the three scenarios are... Figure 3 As shown in this embodiment, the revenue of prosumers and energy operators is compared to that of consumers. Figure 4 , Figure 5 As shown in the figure, the net load comparison chart is as follows: Figure 6 As shown;

[0133] The calculations show the profit results for the three scenarios, as shown in Table 1.

[0134] Table 1

[0135]

[0136] As shown in Table 1, the daily benefits for prosumers in Scenario 3 are RMB 748 and RMB 151 higher than those in Scenario 2 and Scenario 1, respectively. Meanwhile, after taking into account the operating costs of energy operators, the total daily revenue of energy operators in Scenario 3 is RMB 1,600 and RMB 3,700 higher than those in Scenario 2 and Scenario 1, respectively.

[0137] like Figure 5 As shown, scenario 3 can store and consume the most electrical energy when there is surplus photovoltaic output in the system, reducing backfeed power; and when there is a shortage of electricity at night, it can discharge to meet the system's electricity demand, thus playing a better role in peak shaving and valley filling for the overall power grid.

[0138] Example 2:

[0139] In this embodiment, by substituting different example data, the calculation results of example 2 are obtained:

[0140] Calculation example 2:

[0141]

[0142] Figure 7 , 8Figures 9 and 9 respectively illustrate the changes in user revenue, operator revenue, and system load fluctuations in Example 2.

[0143] Example 3:

[0144] In this embodiment, by substituting different example data, the calculation results of example 3 are obtained:

[0145] Calculation example 3:

[0146]

[0147] Figure 10 , Figure 11 , Figure 12 These are graphs showing the changes in user revenue, operator revenue, and system load fluctuations in Example 3.

[0148] Therefore, for energy operators, compared to user-based grid-price trading and the cooperative alliance model and Shapley value method used in most previous research models for profit allocation, the energy game-theoretic control method based on multi-regional sharing proposed in this invention can achieve better economic benefits. For users, on the one hand, they can adjust their energy consumption according to the electricity price in their region; on the other hand, based on their own energy surplus or deficit, users can choose to switch low-voltage side switches and connect to another trading region with a more favorable electricity price to participate in the optimization process. This can effectively protect their privacy while improving overall electricity efficiency, reducing the risk of energy operators maliciously profiting from their competitive advantages, and achieving a balance of interests between the two parties. Simultaneously, while meeting the electricity demand of users within the region, it improves the absorption of photovoltaic power generation, reduces reliance on frequent charging and discharging of energy storage systems, more fully utilizes the time-shifting characteristics of energy storage systems, and reduces the overall net load peak-valley difference within the energy operator's operating area.

[0149] The above embodiments are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above embodiments. Any modifications, alterations, substitutions, combinations, or simplifications made without departing from the spirit and principle of the present invention shall be considered equivalent substitutions and shall be included within the protection scope of the present invention.

Claims

1. A multi-region shared energy game-theoretic control method, characterized in that, Includes the following steps: S1. Initialize producer-consumer and energy operator information, divide into N trading zones according to net load, and determine the purchase and sale of electricity in different zones; The trading area is the area under the jurisdiction of an energy operator where producers and consumers can choose to buy or sell electricity. The amount of electricity to be purchased refers to the total electricity demand of all producers and consumers in the same region who need to purchase electricity. The electricity sales volume refers to the total surplus electricity volume corresponding to all producers and consumers in the same region who need to sell electricity; S2. Construct an energy-sharing entity model, including a comprehensive electricity consumption benefit model for prosumers and a revenue model for energy operators. For prosumers, construct their comprehensive electricity consumption benefit model based on their interest characteristics, and initialize their electricity purchase and sale volume and trading area variables. For energy operators, construct their revenue model based on their interest characteristics, and initialize the internal electricity price, energy storage capacity, and energy storage power within their jurisdiction. The comprehensive electricity consumption benefit model for any prosumer includes: an electricity consumption benefit component and an electricity trading benefit component, as detailed below: The electricity efficiency component is as follows: in, Prosumer i In the region n ,time t Internal electricity consumption efficiency; Prosumer i In the region n ,time t The actual electricity consumption within; Prosumer i In the region n ,time t The efficiency coefficient within the system indicates that the higher the value, the more actively producers and consumers consume electricity to obtain greater benefits. The benefits of constructing an electricity trading system include: in, Prosumer i In the region n ,time t The profit from electricity sales or electricity expenditure during the internal participation in the transaction process; , They represent producers and consumers respectively. i In the region n ,time t The electricity purchase price for inbound operators and the electricity sales price for those operators selling electricity; Indicates producer-consumer i In time t Whether to select in the region n To conduct a transaction, when This indicates that the user has selected this area for trading, otherwise it indicates... ; The revenue models for energy operators include: the electricity dispatch revenue model and the shared energy storage system model; S3. Based on the electricity purchase and sale information submitted by producers and consumers, the energy operator uses the maximization of revenue as the objective function and calculates the scheduling results to obtain the electricity value within the region, the scheduling results of the shared energy storage system, and the energy sharing value within and between regions. S4. Producers and consumers can pursue greater profitability by modifying their purchased and sold electricity volumes and selecting trading regions based on the regional electricity prices provided by energy operators; energy operators can redetermine the configuration capacity of shared energy storage based on the scheduling results of the shared energy storage system, in order to pursue lower operating costs. S5. If the game decision-making results of producers and consumers and energy operators do not change, the transaction result will be used as the final energy transaction regulation plan; otherwise, return to step S3 and continue to repeat the iteration.

2. The energy game-theoretic control method based on multi-regional sharing according to claim 1, characterized in that, The power dispatch benefit model is as follows: in, For operators in the region n ,time t Operating income within the country; , They are respectively regions n Inner t User electricity purchase quota and electricity sales quota for each time period; The toll payable to the power grid when electricity is transmitted through medium and low voltage distribution networks; The shared energy storage system model is as follows: in, For the region n Shared energy storage systems in time t+1 Internal energy storage status; For the region n Shared energy storage system in time t Internal energy storage status; This represents the maximum capacity of the shared energy storage system. For shared energy storage systems in time t Internal charging and discharging power; This represents the maximum charging and discharging power of the shared energy storage system. Indicates the area n Shared energy storage system in time t Internal charging, Indicates the area n Shared energy storage system in time t Internal discharge, Indicates the region n Shared energy storage system in time t It neither charges nor discharges internally.

3. The energy game-theoretic control method based on multi-regional sharing according to claim 1, characterized in that, In step S3, based on the electricity purchase and sale information, the comprehensive electricity consumption benefit model of producers and consumers, and the revenue model of energy operators, the optimal electricity consumption is obtained by taking the first derivative of the revenue function of producers and consumers with respect to electricity consumption and making it equal to zero. This optimal electricity consumption is then input into the revenue function of energy operators, and the electricity value within the region, the capacity and charge / discharge status of the shared energy storage system, and the energy sharing value between regions are calculated. When the total electricity sales of producers and consumers in a region exceed the total electricity purchases, the region as a whole is in a state of surplus electricity. The energy dispatching process of the energy operator is as follows: First, the surplus electricity currently sold by producers and consumers will be prioritized and dispatched to producers and consumers who currently need to purchase the shortfall in electricity to meet their electricity demand. Secondly, the remaining electricity will be allocated in two ways depending on the situation: one is that if the current electricity price in the region is high and other regions have a demand for electricity, the electricity can be sold to other regions; Secondly, the electricity is stored in a shared energy storage system to prepare for the system to discharge during periods of power shortage; if there is still electricity remaining, the remaining electricity is then fed into the grid. When the total electricity sales of producers and consumers within a region are less than the total electricity purchases, the region as a whole is in a state of power shortage. The power dispatching process of the energy operator is as follows: First, the surplus electricity currently sold by producers and consumers will be prioritized and dispatched to producers and consumers who currently need to purchase the shortfall in electricity to meet their electricity demand. Secondly, there are two dispatching schemes for the shortfall in electricity: one is to purchase electricity from other regions when the purchase price of electricity in other regions is lower than that of the grid, and when other regions have surplus electricity, as much electricity as possible can be purchased from them; the other is to share the energy storage system to discharge electricity to meet the demand. If there is still a shortfall in electricity at this time, electricity will be purchased from the grid to make up for the demand.

4. The energy game-theoretic control method based on multi-regional sharing according to claim 2, characterized in that, The following constraints should be met during the power dispatching process of energy operators: Power balance constraints in each region: Electricity price constraints within each region: in, For time t inner area n Interaction power with the power grid; , For time t Energy input and output power between different areas within the space; , They represent producers and consumers respectively. i In the region n ,time t The purchase price of electricity from the grid and the sales price of electricity.

5. The energy game-theoretic control method based on multi-regional sharing according to claim 4, characterized in that, In step S4, both producers and consumers, as well as energy operators, can modify their own parameters based on the scheduling results to pursue better efficiency; the specific steps are as follows: S4.1 Producers and consumers may reselect a trading area that provides better overall electricity consumption benefits and adjust their own electricity consumption. The process of selecting a trading area and adjusting electricity consumption should meet the following constraints: in, They represent producers and consumers respectively. i In the region n ,time t Minimum and maximum power consumption within the area; S4.

2. Based on the scheduling results in step S3, the energy operator can redetermine the shared energy storage configuration capacity. The energy operator's revenue model takes maximizing power dispatch revenue and minimizing operating and investment costs as its objective function, specifically: in, The operating costs for energy operators when scheduling and optimizing energy across all regions; The toll payable to the power grid when electricity is transmitted through a high-voltage transmission network, when the region... n When China's demand for electricity exceeds its supply for sale, the amount of electricity that needs to be transmitted through the high-voltage power grid is equal to the amount of energy received from other regions. The investment cost required by energy operators for energy storage equipment in the region; For the region n Annualized investment cost per unit capacity of energy storage equipment; For the region n The cost per unit power of energy storage equipment; The discount rate; For the region n The service life of medium-sized energy storage equipment.

6. The energy game-theoretic control method based on multi-regional sharing according to claim 5, characterized in that, In step S5, based on the recalculated producer-consumer selection results and energy storage capacity configuration results, it is determined whether the decision results have changed compared with the previous comparison. If the decision result changes, return to step S3 to continue iterative calculation until the decision result no longer changes; if the decision result is the same, the decision result of this transaction will be used as the final energy trading control plan.

7. A game-theoretic control device based on multi-regional energy sharing, based on any one of claims 1 to 6, characterized in that: The device includes: The determination unit is used to determine the information of producers and consumers participating in regional energy sharing, including their selected trading area variables and actual electricity consumption; and to determine the information of energy operators participating in regional energy sharing, including their set intra-regional electricity price, energy storage charging and discharging status value, and inter-regional energy sharing value. The unit is used to establish a comprehensive electricity consumption benefit model for producers and consumers and a revenue model for energy operators based on information from producers and consumers and energy operators. It can also transform the relevant parameters by taking derivatives, and finally establish a multi-regional energy sharing game model with the objective function of maximizing the revenue of energy operators and minimizing operating and investment costs. The solution unit is used to solve the multi-region energy sharing game model, determine whether the game iteration has ended, and finally obtain the optimal parameter configuration of the multi-region energy sharing game model so that producers and consumers and energy operators can carry out energy trading regulation based on the obtained optimal parameters.

8. An electronic device comprising a processor, a memory, and a computer program capable of being stored in the memory and executed by the processor, characterized in that, When the electronic device can execute the program, it can implement the steps of the energy game control method based on multi-region sharing as described in any one of claims 1 to 6.

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