Micro-grid collaborative operation method and system based on mixed game

Abstract

The invention discloses a micro-grid cooperative operation method and system based on a mixed game, and the method comprises the steps: carrying out the master-slave game between a shared energy storage system and a comprehensive energy micro-grid polymer, making a price strategy and a service scheme through the shared energy storage system, adjusting an energy consumption behavior through the comprehensive energy micro-grid polymer according to the strategy, obtaining an energy consumption adjustment range, and achieving the cooperative operation of a micro-grid. The cooperative game is implemented in the integrated energy microgrid aggregate based on the energy consumption adjustment range, and the energy production and consumption strategy of each member is optimized through information sharing and cooperative scheduling. The system can balance the demands of all interest subjects, reduce internal conflicts and contradictions of the system, improve the overall stability and reliability of the system, reduce the operation cost of all microgrids and shared energy storage systems through reasonable energy transaction and optimal scheduling, improve the economic benefits, and improve the energy utilization efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of smart grid and distributed energy management, and specifically to a microgrid collaborative operation method and system based on hybrid game. Background Art

[0002] With the acceleration of global energy transformation, integrated energy microgrids, as a new type of power system, improve energy utilization efficiency and promote the development of renewable energy by integrating multiple energy forms (such as electricity, gas, thermal energy, etc.). Shared energy storage, as a key facility in microgrids, further improves the energy balance capability and economic operation efficiency of microgrids by flexibly deploying energy storage resources.

[0003] In the existing technology, although there have been studies on the optimized operation of integrated energy microgrids and shared energy storage, most of them focus on a single optimization goal or a simple game model, which makes it difficult to fully consider the interests of all parties and complex interactions. Traditional centralized control methods are difficult to meet the complex and changeable interaction needs between microgrids, and a single game model is difficult to fully reflect the interest relationship between microgrids. At the same time, the introduction of shared energy storage systems provides new possibilities for the coordinated operation of microgrids, but how to reasonably allocate energy storage resources and coordinate the interests of each microgrid has become an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to provide a microgrid collaborative operation method and system based on hybrid game, which realizes the collaborative optimization operation between multiple microgrids and shared energy storage systems by constructing a hybrid game model including cooperative game and master-slave game.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A microgrid coordinated operation method based on hybrid game, wherein the microgrid coordinated operation steps include:

[0007] Obtain regional energy production, consumption and storage information to build a comprehensive energy microgrid aggregate;

[0008] Obtain pricing strategies for shared energy storage systems in the region;

[0009] Calculate the energy range of the integrated energy microgrid aggregate interacting with the shared energy storage system;

[0010] A master-slave game model is constructed based on the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system and the price strategy of the shared energy storage system, and the gray wolf algorithm is used to solve it. The solution result is used as the adjustment strategy of the integrated energy microgrid aggregate;

[0011] Determine the energy interaction data within the integrated energy microgrid aggregate corresponding to the adjustment strategy of each integrated energy microgrid aggregate, and the internal members of the integrated energy microgrid aggregate use the cooperative game mechanism to optimize the energy production and consumption strategy;

[0012] Based on the optimization results of the internal energy production and consumption strategies of the integrated energy microgrid aggregates corresponding to the adjustment strategies of each integrated energy microgrid aggregate, the optimal energy production and consumption strategies are selected according to actual needs.

[0013] Shared energy storage system is an emerging energy storage model that allows multiple users or entities to share energy storage facilities to optimize energy use, reduce costs and improve the flexibility and reliability of the power grid. The following is a detailed analysis of the shared energy storage system.

[0014] According to the above technical solution, based on the location information of energy production, consumption and energy storage in the region, the K-Means clustering method is used to cluster the energy production, consumption and energy storage in the region respectively, each cluster is an internal member of the integrated energy microgrid aggregate, and the sum of the energy production information or consumption information or energy storage information corresponding to each cluster is calculated as the energy production information or consumption information or energy storage information of the internal members of the corresponding integrated energy microgrid aggregate.

[0015] According to the above technical solution, there is at least one shared energy storage system in the area.

[0016] According to the above technical solution, in the master-slave game model, the shared energy storage system is used as the leader and the integrated energy microgrid aggregate is used as the follower, which is expressed as: G = * (GO∪ZO); L; R +;

[0017] Among them, G represents the game model, GO and ZO represent participants, GO represents the shared energy storage system, ZO represents the integrated energy microgrid aggregate, L represents the strategist, and L = *L GO , L ZO +, R represents the benefit set, L GO The strategy is to buy energy and sell energy. L ZO The strategy is the response of energy load, R = *R GO , R ZO +, R GO is the objective function of participant GO, R ZO is the objective function of participant ZO;

[0018] L ZO The response quantity of the energy load represented by the strategy is the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system, and the interactive energy range includes the minimum energy and maximum energy of the interaction between the integrated energy microgrid aggregate and the shared energy storage system.

[0019] According to the above technical solution, the objective function R of the participant GO is GO :

[0020]

[0021] The objective function R of the participant ZO ZO :

[0022]

[0023] or

[0024] In the formula, R GO is the total revenue of the shared energy storage system, S t is the income from energy sold in time period t, C gt is the interaction cost in time period t, C bt is the cost of purchasing energy in time period t, μ to represents the price of energy sold by the integrated energy microgrid aggregate during time period t, represents the total amount of energy sold by the integrated energy microgrid aggregate in time period t, μ ts represents the price of energy purchased by the integrated energy microgrid aggregate during time period t, It represents the total amount of energy purchased by the integrated energy microgrid aggregate in the time period t. and It is included in the energy scope of the integrated energy microgrid aggregate and the interaction with the shared energy storage system.

[0025] The upper layer of the master-slave game aims to maximize the benefits of the shared energy storage system, while the lower layer aims to maximize the benefits of the integrated energy microgrid aggregate itself, and the overall system optimization is achieved through iterative solution. The shared energy storage system, as the leader, first formulates the price strategy and service plan, and the integrated energy microgrid aggregate, as the follower, adjusts its own energy consumption behavior according to the strategy of the shared energy storage system to achieve a balance of interests between the two parties.

[0026] According to the above technical solution, the optimal energy production and consumption strategy and price strategy determination steps are:

[0027] Based on the price strategy of the integrated energy microgrid aggregate and the shared energy storage system, the solution value of the master-slave game model is constructed to calculate the total energy interacted by each member within the integrated energy microgrid;

[0028] Based on the total energy of the interaction among the internal members, the overall economic benefits of the integrated energy microgrid aggregate are taken as the objective function, and the cooperative game mechanism is used to optimize the energy production and consumption strategies to obtain the corresponding economic benefits of the integrated energy microgrid aggregate as a whole;

[0029] The solution values ​​of all game models and their corresponding economic benefit values ​​of the integrated energy microgrid aggregate are plotted in a coordinate system to select the optimal energy production and consumption strategy and price strategy.

[0030] According to the above technical solution, the Nash negotiation theory is used in the cooperative game mechanism to obtain the optimal economic benefits of the integrated energy microgrid aggregate as a whole;

[0031] The objective function in the cooperative game mechanism is:

[0032] Where M is the number of consumer members in the integrated energy microgrid aggregate; ΔU z is the economic benefit obtained by consumer member z in the integrated energy microgrid aggregate and the economic benefit and value of the members interacting with consumer member z in the integrated energy microgrid aggregate, U0 is the negotiation breakdown point, that is, the economic benefit of consumer member z in the integrated energy microgrid aggregate before the cooperative game, ΔU z -U0 is the benefit value of consumer member z in the integrated energy microgrid aggregate after participating in the cooperative game. The economic benefit obtained by consumer member z in the integrated energy microgrid aggregate is a negative value, and the economic benefit of members interacting with consumer member z in the integrated energy microgrid aggregate is a positive value. The cooperative game part distributes the cooperative benefits through methods such as Nash negotiation theory to ensure that each microgrid can promote the maximization of overall interests while pursuing its own interests.

[0033] The cooperative game mechanism includes constructing a benefit distribution model based on cooperative game, using an iterative heuristic algorithm combined with a linear programming or mixed integer linear programming solver to solve the optimal energy production and consumption strategy within the integrated energy microgrid aggregate.

[0034] According to the above technical solution, the independent transaction income of each member in the integrated energy microgrid aggregator includes:

[0035] The independent trading income E of members in the integrated energy microgrid aggregation with energy production as the type i :

[0036] maxE i =α i R i -F i ;

[0037] The independent transaction income E of members in the integrated energy microgrid aggregation with energy storage as the type j :

[0038] maxE j =α j R j -β j F j ;

[0039] The independent transaction income E of members in the integrated energy microgrid aggregation with consumption as the type z :

[0040] minE z =βF z ;

[0041] Constraints on energy production in the integrated energy microgrid aggregate:

[0042] P min ≤P v ≤P max ;

[0043] In the formula, α i represents the average energy sales price of member i in the integrated energy microgrid aggregation whose type is energy production, R i represents the maximum energy sold by member i in the integrated energy microgrid aggregate of energy production type, F i represents the energy production cost of member i in the integrated energy microgrid aggregate whose class is energy production, α j represents the average energy sales price of member j in the integrated energy microgrid aggregation with energy storage as the type, R j It is expressed as the maximum energy sales of member j in the integrated energy microgrid aggregation with energy storage as the type, β j It is expressed as the average energy purchase cost of member j in the integrated energy microgrid aggregation with energy storage as the type, F j It is expressed as the maximum energy purchase amount of member j in the integrated energy microgrid aggregation with energy storage as the type, P min Indicates the minimum output limit corresponding to energy production, P v Indicates the energy production corresponding to the output, P max Indicates the maximum output limit corresponding to energy production. The constraints of energy storage and power balance belong to the prior art and will not be introduced in detail here.

[0044] Another embodiment is also included, a microgrid cooperative operation system based on hybrid game, including:

[0045] Data acquisition module, used to obtain regional energy production, consumption and energy storage information, build a comprehensive energy microgrid aggregate, and obtain pricing strategies for regional shared energy storage systems;

[0046] The master-slave game module calculates the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system; constructs a master-slave game model based on the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system and the price strategy of the shared energy storage system, and uses the gray wolf algorithm to solve it and adjust the energy consumption information of the integrated energy microgrid aggregate itself;

[0047] The collaborative optimization module determines the energy interaction data within the integrated energy microgrid aggregate corresponding to the adjustment strategy of each integrated energy microgrid aggregate. The internal members of the integrated energy microgrid aggregate use the cooperative game mechanism to optimize the energy production and consumption strategies. Based on the optimization results of the internal energy production and consumption strategies of the integrated energy microgrid aggregate corresponding to the adjustment strategy of each integrated energy microgrid aggregate, the optimal energy production and consumption strategy is selected according to actual needs.

[0048] According to the above technical solution, the collaborative optimization module execution steps include:

[0049] Based on the price strategy of the integrated energy microgrid aggregate and the shared energy storage system, the solution value of the master-slave game model is constructed to calculate the total energy interacted by each member within the integrated energy microgrid;

[0050] Based on the total energy of the interaction among the internal members, the overall economic benefits of the integrated energy microgrid aggregate are taken as the objective function, and the cooperative game mechanism is used to optimize the energy production and consumption strategies to obtain the corresponding economic benefits of the integrated energy microgrid aggregate as a whole;

[0051] The solution values ​​of all game models and their corresponding economic benefit values ​​of the integrated energy microgrid aggregate are plotted in a coordinate system to select the optimal energy production and consumption strategy and price strategy.

[0052] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention implements a master-slave game between the shared energy storage system and the integrated energy microgrid aggregate, the shared energy storage system formulates a price strategy and a service plan, the integrated energy microgrid aggregate adjusts the energy consumption behavior according to the strategy, obtains the energy consumption adjustment range, implements a cooperative game within the integrated energy microgrid aggregate based on the energy consumption adjustment range, and optimizes the energy production and consumption strategies of each member through information sharing and collaborative scheduling. The present invention can balance the needs of various stakeholders, reduce conflicts and contradictions within the system, and improve the overall stability and reliability of the system. At the same time, through reasonable energy trading and optimized scheduling, it reduces the operating costs of each microgrid and shared energy storage system, improves economic benefits, and improves energy utilization efficiency. Through the collaborative optimization operation between multiple microgrids and shared energy storage systems, efficient energy utilization and complementarity are achieved, and energy waste is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0054] Figure 1 It is a flow chart of steps of a microgrid cooperative operation method based on hybrid game of the present invention;

[0055] Figure 2 It is a flow chart of the steps for determining the optimal energy production and consumption strategy and price strategy of the present invention. DETAILED DESCRIPTION

[0056] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] Example 1

[0058] A microgrid coordinated operation method based on hybrid game, wherein the microgrid coordinated operation steps include:

[0059] S1. Obtain the energy production, consumption and energy storage information in the region and construct an integrated energy microgrid aggregate. The specific steps include: based on the location information of energy production, consumption and energy storage in the region, use the K-Means clustering method to cluster the energy production, consumption and energy storage in the region respectively, each cluster is an internal member of the integrated energy microgrid aggregate, and calculate the sum of the energy production information or consumption information or energy storage information corresponding to each cluster as the energy production information or consumption information or energy storage information of the internal members of the corresponding integrated energy microgrid aggregate.

[0060] For example, region A includes energy production 1-5. Based on the location information of energy production 1-5, the K-Means clustering method is used to cluster energy production 1-3 into category A1 and energy production 4-5 into category A2, and then the comprehensive energy production of category A1 and category A2 is calculated respectively.

[0061] S2. Obtain the price strategy of the shared energy storage system in the region; there is at least one shared energy storage system in the region.

[0062] S3. Calculate the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system. Specifically, take the maximum energy and minimum energy of the historical interaction between the integrated energy microgrid aggregate and the shared energy storage system as the endpoints of the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system.

[0063] S4. A master-slave game model is constructed based on the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system and the price strategy of the shared energy storage system, and the gray wolf algorithm is used to solve it. The solution result is used as the adjustment strategy of the integrated energy microgrid aggregate to adjust the energy consumption information of the integrated energy microgrid aggregate itself;

[0064] Among them, in the master-slave game model, the shared energy storage system is regarded as the leader and the integrated energy microgrid aggregate is regarded as the follower, which is expressed as: G = *(GO∪ZO); L; R +;

[0065] Among them, G represents the game model, GO and ZO represent participants, GO represents the shared energy storage system, ZO represents the integrated energy microgrid aggregate, L represents the strategist, and L = *L GO , L ZO +, R represents the benefit set, L GO The strategy is to buy energy and sell energy. L ZO The strategy is the response of energy load, R = *R GO , R ZO +, R GO is the objective function of participant GO, R ZO is the objective function of participant ZO;

[0066] L ZO The response quantity of the energy load represented by the strategy is the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system. The interactive energy range includes the minimum energy and maximum energy of the interaction between the integrated energy microgrid aggregate and the shared energy storage system.

[0067] Among them, the objective function R of participant GO GO :

[0068]

[0069] The objective function R of participant ZO ZO :

[0070]

[0071] or

[0072] In the formula, R GO is the total revenue of the shared energy storage system, S t is the income from energy sold in time period t, C gt is the interaction cost in time period t, C bt is the cost of purchasing energy in time period t, μ to represents the price of energy sold by the integrated energy microgrid aggregate during time period t, represents the total amount of energy sold by the integrated energy microgrid aggregate in time period t, μ ts represents the price of energy purchased by the integrated energy microgrid aggregate during time period t, It represents the total amount of energy purchased by the integrated energy microgrid aggregate in the time period t. and It is included in the energy scope of the integrated energy microgrid aggregate and the interaction with the shared energy storage system.

[0073] If the energy range of the integrated energy microgrid aggregate and the shared energy storage system is ab, then and is any number within ab.

[0074] S5. Determine the energy interaction data within the integrated energy microgrid aggregate corresponding to the adjustment strategy of each integrated energy microgrid aggregate, optimize the energy production and consumption strategy by using the cooperative game mechanism among the members within the integrated energy microgrid aggregate, and select the optimal energy production and consumption strategy according to actual needs. The specific execution steps include:

[0075] S501. Based on the price strategy of the integrated energy microgrid aggregate and the shared energy storage system, the solution value of the master-slave game model is constructed to calculate the total energy of the interaction between each member within the integrated energy microgrid; that is, if the solution value of the master-slave game model is Q1, Q2, Q3, Q4, Q5, Q6, Q7, Q8, Q9, Q10; and Q1-Q10 correspond to and It must be within the range of ab; according to the solution value, Q1-Q10 corresponds to and The total energy interacted by each member within the integrated energy microgrid is solved to be q1-q10.

[0076] S502, based on the total energy of the interactions among the internal members, the economic benefits of the integrated energy microgrid aggregate as a whole are used as the objective function to optimize the energy production and consumption strategies by using the cooperative game mechanism, and obtain the corresponding economic benefits of the integrated energy microgrid aggregate as a whole;

[0077] Among them, the cooperative game mechanism takes the constraints of energy production, power and energy storage of the integrated energy microgrid aggregate and the independent transaction income of each member in the integrated energy microgrid aggregate as the constraints of the cooperative game mechanism, and takes the overall economic benefits of the integrated energy microgrid aggregate as the objective function;

[0078] Objective function in cooperative game mechanism:

[0079] Where M is the number of consumer members in the integrated energy microgrid aggregate; ΔU z is the economic benefit obtained by consumer member z in the integrated energy microgrid aggregate and the economic benefit and value of the members interacting with consumer member z in the integrated energy microgrid aggregate, U0 is the negotiation breakdown point, that is, the economic benefit of consumer member z in the integrated energy microgrid aggregate before the cooperative game, ΔU z-U0 is the benefit value improved by consumer member z in the integrated energy microgrid aggregate after participating in the cooperative game. The economic benefit obtained by consumer member z in the integrated energy microgrid aggregate is a negative value, and the economic benefit of members with whom consumer member z interacts in the integrated energy microgrid aggregate is a positive value.

[0080] The independent trading benefits of each member in the integrated energy microgrid aggregation include:

[0081] The independent trading income E of members in the integrated energy microgrid aggregation with energy production as the type i :

[0082] maxE i =α i R i -F i ;

[0083] The independent transaction income E of members in the integrated energy microgrid aggregation with energy storage as the type j :

[0084] maxE j =α j R j -β j F j ;

[0085] The independent transaction income E of members in the integrated energy microgrid aggregation with consumption as the type z :

[0086] minE z =βF z ;

[0087] Constraints on energy production in the integrated energy microgrid aggregate:

[0088] P min ≤P v ≤P max ;

[0089] In the formula, α i represents the average energy sales price of member i in the integrated energy microgrid aggregation whose type is energy production, R i represents the maximum energy sold by member i in the integrated energy microgrid aggregate of energy production type, F i represents the energy production cost of member i in the integrated energy microgrid aggregate whose class is energy production, α j represents the average energy sales price of member j in the integrated energy microgrid aggregation with energy storage as the type, R j It is expressed as the maximum energy sales of member j in the integrated energy microgrid aggregation with energy storage as the type, β jIt is represented by the average energy purchase cost of member j in the integrated energy microgrid aggregation with energy storage as the type, F j It is expressed as the maximum energy purchase amount of member j in the integrated energy microgrid aggregation with energy storage as the type, P min Indicates the minimum output limit corresponding to energy production, P v Indicates the energy production corresponding to the output, P max Indicates the maximum output limit corresponding to energy production.

[0090] S503. Plot the solution values ​​of all game models and their corresponding economic benefit values ​​of the integrated energy microgrid aggregate as a whole in a coordinate system. The statistical analysis method or the method of plotting functions to find extreme values ​​can be used to select the optimal energy production and consumption strategy and price strategy based on actual conditions.

[0091] Example 2

[0092] A microgrid cooperative operation system based on hybrid game, comprising:

[0093] Data acquisition module, used to obtain regional energy production, consumption and energy storage information, build a comprehensive energy microgrid aggregate, and obtain pricing strategies for regional shared energy storage systems;

[0094] The master-slave game module calculates the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system; constructs a master-slave game model based on the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system and the price strategy of the shared energy storage system, and uses the gray wolf algorithm to solve it and adjust the energy consumption information of the integrated energy microgrid aggregate itself;

[0095] The collaborative optimization module determines the energy interaction data within the integrated energy microgrid aggregate corresponding to the adjustment strategy of each integrated energy microgrid aggregate. The internal members of the integrated energy microgrid aggregate use the cooperative game mechanism to optimize the energy production and consumption strategies. Based on the optimization results of the internal energy production and consumption strategies of the integrated energy microgrid aggregate corresponding to the adjustment strategy of each integrated energy microgrid aggregate, the optimal energy production and consumption strategy is selected according to actual needs.

[0096] The execution steps of the collaborative optimization module include:

[0097] Based on the price strategy of the integrated energy microgrid aggregate and the shared energy storage system, the solution value of the master-slave game model is constructed to calculate the total energy interacted by each member within the integrated energy microgrid;

[0098] Based on the total energy of the interaction among the internal members, the overall economic benefits of the integrated energy microgrid aggregate are taken as the objective function, and the cooperative game mechanism is used to optimize the energy production and consumption strategies to obtain the corresponding economic benefits of the integrated energy microgrid aggregate as a whole;

[0099] The solution values ​​of all game models and their corresponding economic benefit values ​​of the integrated energy microgrid aggregate are plotted in a coordinate system to select the optimal energy production and consumption strategy and price strategy.

[0100] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0101] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A microgrid cooperative operation method based on hybrid game, characterized in that: The steps of microgrid coordinated operation include: Obtain regional energy production, consumption and storage information to build a comprehensive energy microgrid aggregate; Obtain pricing strategies for shared energy storage systems in the region; Calculate the energy range of the integrated energy microgrid aggregate interacting with the shared energy storage system; Based on the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system and the price strategy of the shared energy storage system, a master-slave game model is constructed and solved using the Grey Wolf Algorithm. The solution is used as the adjustment strategy of the integrated energy microgrid aggregate. Determine the energy interaction data within the integrated energy microgrid aggregate corresponding to the adjustment strategy of the integrated energy microgrid aggregate, and the internal members of the integrated energy microgrid aggregate use the cooperative game mechanism to optimize the energy production and consumption strategy; Based on the optimization results of the internal energy production and consumption strategies of the integrated energy microgrid aggregate corresponding to the adjustment strategy of the integrated energy microgrid aggregate, the optimal energy production and consumption strategies are selected according to actual needs.

2. A microgrid coordinated operation method based on hybrid game according to claim 1, characterized in that: Based on the location information of energy production, consumption and energy storage in the region, the K-Means clustering method is used to cluster the energy production, consumption and energy storage in the region respectively. Each cluster is an internal member of the integrated energy microgrid aggregate, and the sum of the energy production information or consumption information or energy storage information corresponding to each cluster is calculated as the energy production information or consumption information or energy storage information of the internal members of the corresponding integrated energy microgrid aggregate.

3. A microgrid coordinated operation method based on hybrid game according to claim 1, characterized in that: There is at least one shared energy storage system in the region.

4. A microgrid coordinated operation method based on hybrid game according to claim 1, characterized in that: In the master-slave game model, the shared energy storage system is taken as the leader and the integrated energy microgrid aggregate is taken as the follower, which is expressed as: G = {(GO∪ZO); L; R}; Among them, G represents the game model, GO and ZO represent participants, GO represents the shared energy storage system, ZO represents the integrated energy microgrid aggregate, L represents the strategist, and L = {L GO , L ZO }, R represents the benefit set, L GO The strategy is to buy energy and sell energy. L ZO The strategy is the response of energy load, R = {R GO , R ZO }, R GO is the objective function of participant GO, R ZO is the objective function of participant ZO; L ZO The response quantity of the energy load represented by the strategy is the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system, and the interactive energy range includes the minimum energy and maximum energy of the interaction between the integrated energy microgrid aggregate and the shared energy storage system.

5. A microgrid coordinated operation method based on hybrid game according to claim 4, characterized in that: The objective function R of the participant GO GO : The objective function R of the participant ZO ZO : or In the formula, R GO is the total revenue of the shared energy storage system, S t is the income from energy sold in time period t, C gt is the interaction cost in time period t, C bt is the cost of purchasing energy in time period t, μ to represents the price of energy sold by the integrated energy microgrid aggregate during time period t, represents the total amount of energy sold by the integrated energy microgrid aggregate in time period t, μ ts represents the price of energy purchased by the integrated energy microgrid aggregate during time period t, It represents the total amount of energy purchased by the integrated energy microgrid aggregate in the time period t. and Included in the energy range of integrated energy microgrid aggregates interacting with shared energy storage systems.

6. A microgrid coordinated operation method based on hybrid game according to claim 1, characterized in that: The optimal energy production and consumption strategy and price strategy determination steps are as follows: Based on the price strategy of the integrated energy microgrid aggregate and the shared energy storage system, the solution value of the master-slave game model is constructed to calculate the total energy interacted by each member within the integrated energy microgrid; Based on the total energy of the interaction among the internal members, the overall economic benefits of the integrated energy microgrid aggregate are taken as the objective function, and the cooperative game mechanism is used to optimize the energy production and consumption strategies to obtain the corresponding economic benefits of the integrated energy microgrid aggregate as a whole; The solution values ​​of all game models and their corresponding economic benefit values ​​of the integrated energy microgrid aggregate are plotted in a coordinate system to select the optimal energy production and consumption strategy and price strategy.

7. The microgrid coordinated operation method based on hybrid game according to claim 1, characterized in that: The cooperative game mechanism uses Nash negotiation theory to obtain the optimal economic benefits of the integrated energy microgrid aggregate as a whole; The objective function in the cooperative game mechanism is: Where M is the number of consumer members in the integrated energy microgrid aggregate; ΔU z is the economic benefit obtained by consumer member z in the integrated energy microgrid aggregate and the economic benefit and value of the members interacting with consumer member z in the integrated energy microgrid aggregate, U0 is the negotiation breakdown point, that is, the economic benefit of consumer member z in the integrated energy microgrid aggregate before the cooperative game, ΔU z -U0 is the benefit value improved by consumer member z in the integrated energy microgrid aggregate after participating in the cooperative game. The economic benefit obtained by consumer member z in the integrated energy microgrid aggregate is a negative value, and the economic benefit of members with whom consumer member z interacts in the integrated energy microgrid aggregate is a positive value.

8. The microgrid coordinated operation method based on hybrid game according to claim 1, characterized in that: The independent transaction income of each member in the integrated energy microgrid aggregation includes: The independent trading income E of members in the integrated energy microgrid aggregation with energy production as the type i : maxE i =α i R i -F i ; The independent transaction income E of members in the integrated energy microgrid aggregation with energy storage as the type j : max E j =a j R j -b j F j ; The independent transaction income E of members in the integrated energy microgrid aggregation with consumption as the type z : minE z =βF z ; Constraints on energy production in the integrated energy microgrid aggregate: P min ≤P v ≤P max ; In the formula, α i represents the average energy sales price of member i in the integrated energy microgrid aggregation whose type is energy production, R i represents the maximum energy sold by member i in the integrated energy microgrid aggregate of energy production type, F i represents the energy production cost of member i in the integrated energy microgrid aggregate whose class is energy production, α j represents the average energy sales price of member j in the integrated energy microgrid aggregation with energy storage as the type, R j It is expressed as the maximum energy sales of member j in the integrated energy microgrid aggregation with energy storage as the type, β j It is expressed as the average energy purchase cost of member j in the integrated energy microgrid aggregation with energy storage as the type, F j It is expressed as the maximum energy purchase amount of member j in the integrated energy microgrid aggregation with energy storage as the type, P min Indicates the minimum output limit corresponding to energy production, P v Indicates the energy production corresponding to the output, P max Indicates the maximum output limit corresponding to energy production.

9. A microgrid cooperative operation system based on hybrid game, characterized in that: include: Data acquisition module, used to obtain regional energy production, consumption and energy storage information, build a comprehensive energy microgrid aggregate, and obtain pricing strategies for regional shared energy storage systems; The master-slave game module calculates the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system; constructs a master-slave game model based on the energy range of the interaction between the integrated energy microgrid aggregate and the shared energy storage system and the price strategy of the shared energy storage system, and uses the gray wolf algorithm to solve it, and uses the solution result as the adjustment strategy of the integrated energy microgrid aggregate; The collaborative optimization module determines the energy interaction data within the integrated energy microgrid aggregate corresponding to the adjustment strategy of the integrated energy microgrid aggregate. The internal members of the integrated energy microgrid aggregate use the cooperative game mechanism to optimize the energy production and consumption strategies. Based on the optimization results of the internal energy production and consumption strategies of the integrated energy microgrid aggregate corresponding to the adjustment strategy of the integrated energy microgrid aggregate, the optimal energy production and consumption strategies are selected according to actual needs.

10. A microgrid cooperative operation system based on hybrid game according to claim 9, characterized in that: The collaborative optimization module includes: Based on the price strategy of the integrated energy microgrid aggregate and the shared energy storage system, the solution value of the master-slave game model is constructed to calculate the total energy interacted by each member within the integrated energy microgrid; Based on the total energy of the interaction among the internal members, the overall economic benefits of the integrated energy microgrid aggregate are taken as the objective function, and the cooperative game mechanism is used to optimize the energy production and consumption strategies to obtain the corresponding economic benefits of the integrated energy microgrid aggregate as a whole; The solution values ​​of all game models and their corresponding economic benefit values ​​of the integrated energy microgrid aggregate are plotted in a coordinate system to select the optimal energy production and consumption strategy and price strategy.

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