Virtual power plant resource optimization scheduling method and system based on master-slave cooperative game

Abstract

The invention discloses a virtual power plant resource optimization scheduling method and system based on a master-slave cooperative game, and the method comprises the steps: taking the internal purchase and sale electricity price of a virtual power plant operator and the demand response of an energy storage operator as decision variables externally; a single leader-single follower master-slave game model with simultaneous maximization of benefits of a virtual power plant operator and an energy storage operator as a target function is constructed, a cooperative alliance of a hydrogen energy storage operator and an electrochemical energy storage operator is established inside, and the maximum benefits of the two cooperative parties are achieved in a cooperative game mode. According to the method, optimal scheduling of internal resources is realized, so that benefit distribution of virtual power plant operators and internal resource providers can be balanced, the economic benefit of the virtual power plant is improved, meanwhile, by considering energy interaction of the internal resources, the economic benefit is generated, energy waste is avoided, and the economic benefit is increased. The method has a remarkable positive effect on the structure adjustment of a novel power system and the construction of a diversified power market.

Description

Technical Field

[0001] The present invention relates to the technical field of resource optimization scheduling of virtual power plants, and in particular, to a method and system for optimizing resource scheduling of virtual power plants based on master-slave cooperative game, electronic equipment, and a computer-readable storage medium. Background Art

[0002] With the rapid development of distributed energy such as a large number of distributed power sources, energy storage and controllable loads, the construction of new power systems has ushered in huge challenges. Distributed energy has the characteristics of small capacity, diverse resource types, large quantity and scale, and geographical dispersion, and has certain regulation capabilities. It is of great significance to reasonably and effectively dispatch distributed energy to provide power auxiliary services for the power grid. In order to achieve coordinated control and energy management of various distributed resources, virtual power plants (VPPs) are used as a new form to realize the aggregation control of a large number of distributed energy sources. Through advanced communication technology and control strategies, distributed resources such as photovoltaics, wind power, energy storage, electric vehicles, and user loads are aggregated to participate in power market auxiliary services or participate in load demand response to achieve power grid peak and frequency regulation. When participating in power market auxiliary services, VPPs generally control and dispatch aggregated loads in a refined manner through economic dispatch. According to the electricity price forecast, load forecast, power output forecast and the basic information and constraints of each distributed energy in VPP, the information of the day-ahead electricity energy market and distributed power sources in VPP is comprehensively analyzed to optimize the dispatching decision, formulate VPP economic dispatching plans, interact with the day-ahead electricity energy market externally, and coordinate the dispatching of each distributed power source internally.

[0003] However, the existing dispatching methods mainly focus on how VPP, as an influencer of market electricity prices, can maximize its own operating interests through reasonable economic dispatching, while ignoring how VPP, as an electricity price setter of aggregated energy owners, can enable aggregated energy operators to achieve internal optimal dispatching so that internal energy operators can obtain greater economic benefits. Therefore, it is urgent to provide diversified dispatching strategies within virtual power plants and aggregated energy, so as to achieve an overall win-win situation for virtual power plant operators and energy operators. Summary of the invention

[0004] The present invention provides a virtual power plant resource optimization scheduling method and system based on master-slave cooperative game, electronic equipment, and computer-readable storage medium, which can balance the interest distribution between virtual power plant operators and internal resource providers and improve the economic benefits of virtual power plants. At the same time, by considering the energy interaction of internal resources, it not only generates economic benefits but also avoids energy waste, which has a significant positive effect on the structural adjustment of new power systems and the construction of diversified power markets.

[0005] According to one aspect of the present invention, a virtual power plant resource optimization scheduling method based on master-slave cooperative game is provided, wherein the energy storage operator includes a hydrogen energy storage operator and an electrochemical energy storage operator, including the following contents:

[0006] Construct the revenue objective functions of virtual power plant operators, energy storage operators, hydrogen energy storage operators and electrochemical energy storage operators respectively;

[0007] A master-slave game strategy is adopted to construct a master-slave game model between virtual power plant operators and energy storage operators based on their revenue objective functions.

[0008] A cooperative game strategy is adopted to construct a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on their revenue objective functions.

[0009] Taking the simultaneous maximization of the profits of virtual power plant operators and energy storage operators as the optimization goal, the master-slave game model is solved to obtain the optimal purchase and sale price strategy of the virtual power plant operator and the optimal purchase and sale quantity strategy of the energy storage operator;

[0010] Taking the optimal power purchase and sales strategy of energy storage operators as constraints, the optimal power purchase and sales price strategy as known conditions, and the simultaneous maximization of the profits of hydrogen energy storage operators and electrochemical energy storage operators as the optimization goal, the cooperative game model is solved to obtain the optimal charging and discharging curves of hydrogen energy storage operators and electrochemical energy storage operators respectively;

[0011] Based on the optimal charging and discharging curves of hydrogen energy storage operators and electrochemical energy storage operators, their respective charging and discharging states are controlled respectively.

[0012] Furthermore, the profit objective function of the virtual power plant operator is:

[0013]

[0014] The revenue objective function of the energy storage operator is:

[0015]

[0016] Among them, f VPP represents the total revenue of the virtual power plant operator, f ESO represents the total revenue of the energy storage operator, represents the clearing price of the electricity market at time t, represents the electricity price sold by the virtual power plant operator to the energy storage operator at time t, represents the electricity purchase price of the virtual power plant operator from the energy storage operator at time t, represents the amount of electricity sold by the virtual power plant operator to the day-ahead power market at time t, represents the amount of electricity sold by the virtual power plant operator to the energy storage operator at time t, Represents the amount of electricity purchased by the virtual power plant operator from the energy storage operator at time t.

[0017] Furthermore, the profit objective function of the hydrogen energy storage operator is:

[0018]

[0019] The profit objective function of the electrochemical energy storage operator is:

[0020]

[0021] Among them, C HS represents the revenue of hydrogen energy storage operators, T represents the time period, and P MCFC,sell (t) represents the electric power sold by the fuel cell to the virtual power plant at time t, η HS Indicates the hydrogen storage efficiency of the hydrogen storage tank, S HS (t) represents the storage capacity of the hydrogen storage tank at time t, represents the input power used for the electrolyzer when the hydrogen energy storage operator purchases electricity from the virtual power plant operator at time t, represents the additional revenue allocated to hydrogen energy storage operators under the cooperative game strategy, P ELmin and P ELmax They represent the lower and upper limits of the electrolytic cell input power, respectively. It represents the input power for the electrolyzer from the excess electricity of the electrochemical energy storage operator at time t, and They represent the lower and upper limits of the hydrogen storage power of the hydrogen storage tank, P HS (t) represents the hydrogen storage power of the hydrogen storage tank at time t, and They represent the minimum and maximum effective utilization rates of the hydrogen storage tank, S HS (t) represents the storage capacity of the hydrogen storage tank at time t, Q HS Indicates the construction capacity of the hydrogen storage tank, and They represent the lower and upper limits of the fuel cell’s hydrogen input power, represents the input hydrogen power of the fuel cell at time t, P MCFC,sellmin and P MCFC,sellmax They represent the lower and upper limits of the electric power that the fuel cell can sell to the virtual power plant, P MCFC,sell (t) represents the electric power used by the fuel cell to sell electricity to the virtual power plant at time r, C storage represents the revenue of electrochemical energy storage operators, represents the discharge power of the electrochemical energy storage device sold to the virtual power plant operator at time t, Es,t represents the energy stored in the electrochemical energy storage device at time t, represents the power purchased by the electrochemical energy storage device from the virtual power plant operator at time t, represents the additional revenue allocated to the electrochemical energy storage operator under the cooperative game strategy, P char (t) represents the charging power of the electrochemical energy storage device, P dischar (t) represents the discharge power of the electrochemical energy storage device, s char and dischar Boolean variables representing the charging and discharging states of the electrochemical energy storage device, and Respectively represent the maximum charging power and maximum discharging power of the electrochemical energy storage device, SOC min and SOC max They represent the lower and upper limits of the state of charge of the electrochemical energy storage device, respectively. SOC(t) represents the state of charge of the electrochemical energy storage device at time t. s,min and E s,max Respectively represent the lower and upper limits of the capacity of electrochemical energy storage devices.

[0022] Furthermore, in the master-slave game strategy, the virtual power plant operator acts as a leader and the energy storage operator acts as a follower, wherein the master-slave game model is:

[0023]

[0024] Among them, Ω1 represents the master-slave game model, VPP represents the virtual power plant operator, and ESO represents the energy storage operator.

[0025] Furthermore, in the cooperative game strategy, the hydrogen energy storage operator and the electrochemical energy storage operator establish a cooperative alliance through interactive energy sharing. The alliance as a whole conducts electricity transactions with the outside world through the energy storage operator. The electrochemical energy storage operator allocates idle or excess electricity to the hydrogen energy storage operator, and the hydrogen energy storage operator obtains additional income through hydrogen production and heat generation. The cooperative game model is:

[0026]

[0027] Among them, Ω2 represents the cooperative game model, HS represents the hydrogen energy storage operator, and cell represents the electrochemical energy storage operator.

[0028] Furthermore, the optimal power purchase and sales strategy of the energy storage operator is expressed as a constraint condition:

[0029]

[0030] in, and They represent the optimal amount of electricity purchased and sold by the virtual power plant operator to the energy storage operator, represents the optimal power sold by the fuel cell to the virtual power plant at time t, represents the optimal discharge power of the electrochemical energy storage device to sell electricity to the virtual power plant operator at time t, represents the optimal input power for the electrolyzer when the hydrogen energy storage operator purchases electricity from the virtual power plant operator at time t, It represents the optimal power purchased by the electrochemical energy storage device from the virtual power plant operator at time t.

[0031] Furthermore, the excess electricity delivered by the electrochemical energy storage operator to the hydrogen energy storage operator is obtained through historical data. The excess electricity is converted into thermal energy through the hydrogen boiler model and sold to the thermal load to obtain additional revenue. The additional revenue is then distributed to the hydrogen energy storage operator and the electrochemical energy storage operator using a distribution strategy based on the Shaplay value.

[0032] In addition, the present invention also provides a virtual power plant resource optimization scheduling system based on master-slave cooperative game, including:

[0033] A revenue objective function construction module, used to construct the revenue objective functions of virtual power plant operators, energy storage operators, hydrogen energy storage operators and electrochemical energy storage operators respectively;

[0034] A master-slave game model construction module is used to construct a master-slave game model between a virtual power plant operator and an energy storage operator based on the revenue objective function of the virtual power plant operator and the energy storage operator using a master-slave game strategy;

[0035] A cooperative game model building module is used to build a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on the revenue objective functions of hydrogen energy storage operators and electrochemical energy storage operators using cooperative game strategies;

[0036] The master-slave game model solving module is used to solve the master-slave game model with the optimization goal of maximizing the profits of the virtual power plant operator and the energy storage operator at the same time, and obtain the optimal purchase and sale price strategy of the virtual power plant operator and the optimal purchase and sale power strategy of the energy storage operator;

[0037] The cooperative game model solving module is used to solve the cooperative game model with the optimal power purchase and sales strategy of the energy storage operator as the constraint condition, the optimal power purchase and sales price strategy as the known condition, and the simultaneous maximization of the revenue of the hydrogen energy storage operator and the electrochemical energy storage operator as the optimization goal, and obtain the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator respectively;

[0038] The internal resource optimization scheduling module is used to control the charging and discharging states of each other based on the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator.

[0039] In addition, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor executes the steps of the above method by calling the computer program stored in the memory.

[0040] In addition, the present invention also provides a computer-readable storage medium for storing a computer program for optimizing the scheduling of virtual power plant resources based on a master-slave cooperative game, wherein the computer program executes the steps of the method described above when running on a computer.

[0041] The present invention has the following beneficial effects:

[0042] The virtual power plant resource optimization scheduling method based on master-slave cooperative game of the present invention uses the internal purchase and sale electricity price of the virtual power plant operator and the demand response of the energy storage operator as decision variables externally, constructs a single-leader-single-follower master-slave game model with the objective function of maximizing the benefits of the virtual power plant operator and the energy storage operator at the same time; internally, a cooperative alliance of hydrogen energy storage operators and electrochemical energy storage operators is established, and through cooperative game, the optimal scheduling of internal resources is achieved with the goal of achieving the maximum interests of both parties, thereby balancing the interest distribution of virtual power plant operators and internal resource providers and improving the economic benefits of virtual power plants. At the same time, by considering the energy interaction of internal resources, it not only generates economic benefits but also avoids energy waste, which has a significant positive effect on the structural adjustment of new power systems and the construction of diversified power markets.

[0043] In addition, the virtual power plant resource optimization scheduling system based on master-slave cooperative game of the present invention also has the above advantages.

[0044] In addition to the above-described purposes, features and advantages, the present invention has other purposes, features and advantages. The present invention will be further described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The drawings constituting a part of this application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0046] Figure 1 It is a flow chart of a virtual power plant resource optimization scheduling method based on master-slave cooperative game in a preferred embodiment of the present application.

[0047] Figure 2It is a schematic diagram of the module structure of a virtual power plant resource optimization and scheduling system based on master-slave cooperative game in another embodiment of the present application. DETAILED DESCRIPTION

[0048] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0049] Reference Figure 1 The preferred embodiment of the present application provides a virtual power plant resource optimization scheduling method based on master-slave cooperative game, wherein the energy storage operator includes a hydrogen energy storage operator and an electrochemical energy storage operator, including the following contents:

[0050] Step S1: constructing the revenue objective functions of virtual power plant operators, energy storage operators, hydrogen energy storage operators and electrochemical energy storage operators respectively;

[0051] Step S2: Using a master-slave game strategy based on the revenue objective functions of the virtual power plant operator and the energy storage operator, a master-slave game model between the virtual power plant operator and the energy storage operator is constructed;

[0052] Step S3: Using a cooperative game strategy based on the revenue objective functions of hydrogen energy storage operators and electrochemical energy storage operators, a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators is constructed;

[0053] Step S4: Taking the simultaneous maximization of the profits of the virtual power plant operator and the energy storage operator as the optimization goal, the master-slave game model is solved to obtain the optimal purchase and sale price strategy of the virtual power plant operator and the optimal purchase and sale power strategy of the energy storage operator;

[0054] Step S5: Taking the optimal power purchase and sales strategy of the energy storage operator as a constraint condition, taking the optimal power purchase and sales price strategy as a known condition, and taking the simultaneous maximization of the revenue of the hydrogen energy storage operator and the electrochemical energy storage operator as the optimization goal, the cooperative game model is solved to obtain the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator respectively;

[0055] Step S6: Controlling the charge and discharge states of each based on the optimal charge and discharge curves of the hydrogen energy storage operator and the electrochemical energy storage operator.

[0056] It can be understood that the virtual power plant resource optimization scheduling method based on master-slave cooperative game in this embodiment uses the internal purchase and sale electricity price of the virtual power plant operator and the demand response of the energy storage operator as decision variables externally, and constructs a single-leader-single-follower master-slave game model with the objective function of maximizing the profits of the virtual power plant operator and the energy storage operator. Internally, a cooperative alliance of hydrogen energy storage operators and electrochemical energy storage operators is established, and through cooperative game, the optimal scheduling of internal resources is achieved with the goal of achieving the maximum interests of both parties. This can balance the distribution of interests between virtual power plant operators and internal resource providers, and improve the economic benefits of virtual power plants. At the same time, by considering the energy interaction of internal resources, it not only generates economic benefits but also avoids energy waste, which has a significant positive effect on the structural adjustment of new power systems and the construction of diversified power markets.

[0057] It can be understood that the market rules for virtual power plants and energy storage operators to participate in the electricity market include that the energy storage equipment operated by the energy storage operator integrates energy generation and power consumption, that is, the energy storage operator gives priority to its own supply and demand balance. When its own power generation is insufficient, it purchases electricity from the virtual power plant operator; otherwise, it sells excess electricity to the virtual power plant operator. The virtual power plant operator will interact with the external large power grid and submit the bid price and bid power in the day-ahead market to the electricity market as an influencer of market prices. It will influence the spot market clearing price through bidding decisions and decide the internal purchase and sale price of energy storage operators based on the market clearing price to maximize the total operating income of the virtual power plant. Among them, the profit objective function of the virtual power plant operator is:

[0058]

[0059] The revenue objective function of the energy storage operator is:

[0060]

[0061] Among them, f VPP represents the total revenue of the virtual power plant operator, f ESO represents the total revenue of the energy storage operator, represents the clearing price of the electricity market at time t, represents the electricity price sold by the virtual power plant operator to the energy storage operator at time t, represents the electricity purchase price of the virtual power plant operator from the energy storage operator at time t, represents the amount of electricity sold by the virtual power plant operator to the day-ahead power market at time t, represents the amount of electricity sold by the virtual power plant operator to the energy storage operator at time t, It represents the amount of electricity purchased by the virtual power plant operator from the energy storage operator at time t, and T represents the time period, such as the settlement period.

[0062] In addition, the hydrogen energy storage power generation system of the hydrogen energy storage operator includes four parts, namely: electrolyzer hydrogen production system, hydrogen storage tank hydrogen storage system, fuel cell hydrogen power generation system and hydrogen boiler heating system. The operating mechanism of the hydrogen energy storage power generation system is: first meet its own load demand, electrolyze water to produce hydrogen through surplus electricity, store it in the hydrogen storage tank to provide energy storage guarantee for the system, and then use fuel cells or other conversion methods to convert hydrogen energy into electricity to meet self-use or online trading when electricity is needed. During the low electricity consumption period, hydrogen energy can also be converted into heat energy through hydrogen boilers to supply heat load. Due to the cooperative game mechanism, hydrogen energy storage can not only purchase and sell electricity from virtual power plants as part of the energy storage operator alliance, but also receive idle electricity or excess electricity from electrochemical energy storage parties to convert into hydrogen energy to generate additional income. The operating mechanism of the electrochemical energy storage operator includes: first meet its own load demand. When the virtual power plant purchases electricity at a low price, the electrochemical energy storage operator purchases electricity from the virtual power plant operator for charging. When the virtual power plant sells electricity at a high price, the electrochemical energy storage operator discharges and sells electricity to the virtual power plant operator. Due to the cooperative game mechanism, electrochemical energy storage parties can not only be part of the energy storage operator alliance, but also provide excess electricity to hydrogen energy storage operators.

[0063] Among them, the electrolytic cell model can be expressed as: is the input power for the electrolyzer purchased from the virtual power plant operator at time t, is the input power for the electrolyzer from the excess electricity of the electrochemical energy storage operator at time t, V h is the hydrogen production rate of the electrolyzer, η EL is the electrolysis efficiency of the electrolytic cell, H hv is the calorific value of hydrogen.

[0064] The fuel cell model can be expressed as: P MCFC,sell (t) is the power sold by the fuel cell to the virtual power plant at time t, P MCFC,toHS (t) is the electric power delivered by the fuel cell to the hydrogen storage tank at time t, η e is the power generation efficiency of the fuel cell, Q MCFC,sell (t) is the thermal power of the fuel cell selling heat to the heat load at time t, η b is the heating efficiency of the fuel cell, V hf (t) is the rate of hydrogen delivered to the fuel cell at time t.

[0065] The hydrogen boiler model can be expressed as: {Q hb (t) = V hb (t)Hhv η hb , Q hb (t) is the output thermal power of the hydrogen boiler at time t, V hb (t) is the hydrogen consumption of the hydrogen boiler at time t, η hb It is the heating efficiency of the hydrogen boiler. When the hydrogen energy storage power generation system meets the electricity load demand or is in the low electricity consumption period, and there is a demand for heat load at this time, the excess hydrogen can be converted into heat energy to meet the balance of heat supply and demand to obtain additional benefits.

[0066] The hydrogen storage tank model can be expressed as: V HS (t) is the rate at which the hydrogen storage tank stores hydrogen during period t, S HS (t) is the storage capacity of the hydrogen storage tank at time t, S HS (t-1) is the storage capacity of the hydrogen storage tank at time t-1.

[0067] In addition, the constraints of the electrolytic cell model are the upper and lower limits of the electrolytic cell input power: The constraints of the hydrogen storage tank model are the upper and lower limits of hydrogen storage power and the upper and lower limits of storage capacity: The constraints of the fuel cell model are the upper and lower limits of the input power and the upper and lower limits of the power sold to the virtual power plant:

[0068] The electrochemical energy storage equipment of the electrochemical energy storage operator is a lithium-ion battery, and the output model of the lithium-ion battery can be expressed as: Among them, P SC (t) represents the charging power of the electrochemical energy storage device at time t, represents the power purchased by the electrochemical energy storage device from the virtual power plant operator at time t, represents the discharge power of the electrochemical energy storage device sold to the virtual power plant operator at time t, represents the transmission power of the electrochemical energy storage device discharging to the hydrogen energy storage operator at time t, They represent the charge and discharge efficiency of electrochemical energy storage devices, P USER (t) represents the self-used electric power of the electrochemical energy storage device at time t, E s,t Indicates the energy stored in the electrochemical energy storage device at time t. In addition, the constraints of the lithium battery energy storage device are: the charge and discharge power of the lithium battery device should not exceed the maximum charge and discharge power of the device, and the battery can only work in one state at the same time, which can be expressed as: in, Indicates the maximum charging power and maximum discharging power of the electrochemical energy storage device, s char 、s discharRepresents a Boolean variable, which is used to prevent the energy storage device from charging and discharging at the same time during the t period; the state of charge of the lithium battery device should not exceed the upper and lower limits of the device: {SOC min ≤SOC(t)≤SOC max ; The energy stored in lithium battery equipment should not exceed the upper limit of the equipment capacity: {E s，min ≤E s，t ≤E s，max .

[0069] Therefore, the profit objective function of the hydrogen energy storage operator can be expressed as:

[0070]

[0071] The profit objective function of the electrochemical energy storage operator is:

[0072]

[0073] Among them, C HS represents the revenue of hydrogen energy storage operators, T represents the time period, and P MCFC,sell (t) represents the electric power sold by the fuel cell to the virtual power plant at time t, η HS Indicates the hydrogen storage efficiency of the hydrogen storage tank, S HS (t) represents the storage capacity of the hydrogen storage tank at time t, represents the input power used for the electrolyzer when the hydrogen energy storage operator purchases electricity from the virtual power plant operator at time t, represents the additional revenue allocated to hydrogen energy storage operators under the cooperative game strategy, P ELmin and P ELmax They represent the lower and upper limits of the electrolytic cell input power, respectively. It represents the input power for the electrolyzer from the excess electricity of the electrochemical energy storage operator at time t, and They represent the lower and upper limits of the hydrogen storage power of the hydrogen storage tank, P HS (t) represents the hydrogen storage power of the hydrogen storage tank at time t, and They represent the minimum and maximum effective utilization rates of the hydrogen storage tank, S HS (t) represents the storage capacity of the hydrogen storage tank at time t, Q HS Indicates the construction capacity of the hydrogen storage tank, and They represent the lower and upper limits of the fuel cell’s hydrogen input power, represents the input hydrogen power of the fuel cell at time t, P MCFC,sellmin and P MCFC,sellmax They represent the lower and upper limits of the electric power that the fuel cell can sell to the virtual power plant, P MCFC,sell(t) represents the electric power used by the fuel cell to sell electricity to the virtual power plant at time r, C storage represents the revenue of electrochemical energy storage operators, represents the discharge power of the electrochemical energy storage device sold to the virtual power plant operator at time t, E s,t represents the energy stored in the electrochemical energy storage device at time t, represents the power purchased by the electrochemical energy storage device from the virtual power plant operator at time t, represents the additional revenue allocated to the electrochemical energy storage operator under the cooperative game strategy, P char (t) represents the charging power of the electrochemical energy storage device, P dischar (t) represents the discharge power of the electrochemical energy storage device, s char and dischar Boolean variables representing the charging and discharging states of the electrochemical energy storage device, and Respectively represent the maximum charging power and maximum discharging power of the electrochemical energy storage device, SOC min and SOC max They represent the lower and upper limits of the state of charge of the electrochemical energy storage device, respectively. SOC(t) represents the state of charge of the electrochemical energy storage device at time t. s,min and E s,max Respectively represent the lower and upper limits of the capacity of electrochemical energy storage devices.

[0074] It can be understood that in the master-slave game strategy, the virtual power plant operator acts as a leader and the energy storage operator acts as a follower. Specifically, the leader is the virtual power plant operator, which takes its profit maximization as its objective function, and decides the internal optimal purchase and sale price through the market clearing price and energy storage electricity demand to maximize its benefits; the follower is the energy storage operator, which takes the maximum profit of the energy storage operator as its objective function, responds to the demand according to the purchase and sale price signal decided by the virtual power plant operator, and decides its own purchase and sale amount to maximize its benefits; at the same time, the demand response decided by the energy storage operator will affect the profit of the virtual power plant operator, thus forming a master-slave game strategy with a single leader and a single follower. In the master-slave game process, the virtual power plant operator, as the leader, takes the lead in formulating the internal purchase and sale electricity price for the energy storage operator through the historical clearing price of the electricity market on the previous day. The energy storage operator, as the follower, adjusts its own charging and discharging curve according to the internal purchase and sale electricity price and reports its own electricity purchase and sale demand. The virtual power plant operator then adjusts its own internal purchase and sale electricity price according to the reported electricity purchase and sale demand. The energy storage operator continues to adjust its own electricity purchase and sale demand according to the new purchase and sale electricity price. Both parties aim to maximize their own interests and repeat the game process until an equilibrium solution appears, that is, both parties are concentrated on one point and this point maximizes the interests of all participants. Then the game process can be ended and the optimal game solution can be output.

[0075] The master-slave game model mainly includes three elements: participants, strategies and benefits. The participants in the master-slave game refer to the entities that make decisions in the master-slave game, which are virtual power plant operators and energy storage operators, represented by VPP and ESO respectively; the participant strategy refers to the strategy set selected by the two parties in the game process. Let the strategy set of the leader virtual power plant operator be Let the strategy set of the follower energy storage operator be The player's profit refers to the profit obtained by both parties in the game process. Let the profit set be f = {f VPP ,f ESO}. Therefore, the master-slave game model can be expressed as:

[0076]

[0077] Among them, Ω1 represents the master-slave game model, VPP represents the virtual power plant operator, and ESO represents the energy storage operator.

[0078] It can be understood that the cooperative game strategy means that the energy storage operator is a cooperative alliance, and only dispatches the charging and discharging capacity from different energy storage parties, including hydrogen energy storage and electrochemical energy storage. In the absence of a cooperative alliance, the construction cost of hydrogen energy storage is high, and the cost of power generation is much greater than that of electrochemical energy storage. If you simply participate in the master-slave game as a follower, you will not be able to compete with the other followers, and most of the energy storage equipment gathered in the virtual power plant is idle. If the battery cannot be released in time after charging, it will cause the time decay of the lithium battery storage capacity. Therefore, both hydrogen energy storage operators and electrochemical energy storage operators hope to maximize their own benefits while maximizing overall benefits. Therefore, in the cooperative game strategy, hydrogen energy storage operators and electrochemical energy storage operators establish a cooperative alliance through energy interactive sharing. The alliance as a whole conducts electricity transactions with the outside through energy storage operators. Electrochemical energy storage operators allocate idle electricity or excess electricity to hydrogen energy storage operators. Hydrogen energy storage operators obtain additional benefits through hydrogen production and heat generation, thereby fully improving the flexibility and economy of energy storage system operation.

[0079] Among them, the cooperative game model mainly includes three elements: participants, strategies and benefits. The cooperative game participants refer to the entities that make decisions in the cooperative game, which are hydrogen energy storage operators and electrochemical energy storage operators, which can be expressed as N = {HS, cell}; the participant strategy refers to the strategy set selected by the two parties in the game process. Let the strategy set of the hydrogen energy storage party be expressed as The strategy set of the electrochemical energy storage party is expressed as The player's profit refers to the profit obtained by both parties in the game process. Let the profit set be expressed as f = {C HS ,C storage}. Therefore, the cooperative game model can be expressed as:

[0080]

[0081] Among them, Ω2 represents the cooperative game model, HS represents the hydrogen energy storage operator, and cell represents the electrochemical energy storage operator.

[0082] It can be understood that the optimization goal is to maximize the benefits of virtual power plant operators and energy storage operators at the same time. Specifically, the differential algorithm is used to solve the master-slave game model to obtain the optimal purchase and sale price strategy of the virtual power plant operator and the optimal purchase and sale strategy of the energy storage operator. Among them, the differential algorithm mainly solves nonlinear optimization problems, has fewer control parameters and higher convergence efficiency, and belongs to the existing algorithm. The specific solution process will not be repeated here. As an example, the simplified solution process is as follows: first input data and parameters, take the day-ahead clearing electricity price in the electricity market as a known quantity, and when calculating the leader's profit, it is necessary to provide the follower's demand response, that is, the amount of electricity purchased and sold. When calculating the follower's profit, it is necessary to provide the purchase and sale price set by the leader, and take the constraint condition as the parameter boundary limit; then, the virtual power plant operator provides the energy storage operator with the purchase and sale price information, and the lower-level energy storage operator makes its own demand response, that is, the electricity demand signal, through the initial electricity price signal; then, the upper-level virtual power plant operator accepts the demand response information of the lower-level energy storage operator, and takes the maximum profit of the upper-level virtual power plant function as the objective function value, and continuously mutates, crosses, and selects; then, by comparing with the optimal result of the previous round of iterations, it is determined whether the algorithm has reached the number of iterations. If it has not reached the number of game times, the above process is repeated. If the difference is less than the model accuracy, it is a game equilibrium solution, and the process can be ended, and the optimal purchase and sale price strategy of the upper-level virtual power plant operator and the optimal purchase and sale electricity strategy of the lower-level energy storage operator are output. Among them, the optimal solution M1 of the master-slave game model can be expressed as:

[0083]

[0084] in, The internal optimal pricing strategy formulated for the virtual power plant is guided by the electricity price signal, so that the energy storage operator can spontaneously adjust its own charging and discharging time periods and charging and discharging quantities according to the electricity price signal, and finally output the optimal charging and discharging quantity as follows:

[0085] It can be understood that since the cooperative game model is subject to the constraints of the agreement, the optimal power purchase and sales strategy of the energy storage operator is required as a constraint condition, which can be expressed as:

[0086]

[0087] in, and They represent the optimal amount of electricity purchased and sold by the virtual power plant operator to the energy storage operator, represents the optimal power sold by the fuel cell to the virtual power plant at time t, represents the optimal discharge power of the electrochemical energy storage device to sell electricity to the virtual power plant operator at time t, represents the optimal input power for the electrolyzer when the hydrogen energy storage operator purchases electricity from the virtual power plant operator at time t, It represents the optimal power purchased by the electrochemical energy storage device from the virtual power plant operator at time t.

[0088] Then, taking the optimal electricity purchase and sales strategy of the energy storage operator as the constraint condition, the optimal electricity purchase and sales price strategy as the known condition, and maximizing the profits of the hydrogen energy storage operator and the electrochemical energy storage operator as the optimization goal, the particle swarm-based optimization algorithm is used to solve the cooperative game model to obtain the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator. Among them, the particle swarm-based optimization algorithm belongs to the existing algorithm, and the specific solution principle will not be repeated here. As an example, the process of solving the cooperative game model by the particle swarm-based optimization algorithm is as follows: initialize the particle swarm, take the charging and discharging output of hydrogen energy storage and electrochemical energy storage at time t as random particles, set the initial position to be randomly selected in the solution space set, and set the initial speed to a random value; update the individual best position, for each particle, according to the objective function value of its current position, update its individual best position, if the function value of the current position is better than the individual best position, then set the current position to the individual best position; update the group best position, for the entire particle swarm, according to the individual best position of each particle, select the global best position, that is, the position with the best fitness among all particles; by repeating the above steps until the stop condition is met, such as reaching the maximum number of iterations or the fitness value is close enough to the optimal solution, the optimal solution can be output, that is, the optimal charging and discharging curve of the hydrogen energy storage operator and the electrochemical energy storage operator. Among them, the optimal solution M2 of the cooperative game model can be expressed as:

[0089]

[0090] in, The optimal charge and discharge curve for hydrogen energy storage, Optimal charge and discharge curves for electrochemical energy storage, To achieve the best benefits for hydrogen energy storage operators under cooperative game, The optimal benefits of electrochemical energy storage operators under cooperative game are obtained. Finally, the charging and discharging states of hydrogen energy storage operators and electrochemical energy storage operators are controlled according to the optimal charging and discharging curves, so as to issue the optimal dispatching commands to the internal resources of energy storage operators.

[0091] In addition, considering that in actual dispatching, due to factors such as power transmission loss and battery capacity loss, electrochemical energy storage operators will have a margin for charging and discharging. According to historical data, under the required charging and discharging curve, the excess electricity of electrochemical energy storage operators can be sent to hydrogen energy storage operators, and additional income can be obtained by converting hydrogen into heat energy. Then, the benefits are distributed according to the profit distribution rules in the cooperative game to maximize the interests of both parties. Specifically, the solution for the excess electricity sent by electrochemical energy storage operators to hydrogen energy storage operators is obtained through historical data. Convert it into heat energy through the hydrogen boiler model, and then sell it to heat load to obtain additional income According to the principle of interest distribution in cooperative games, for example, the distribution strategy based on Shaplay value can be used to distribute and That is, hydrogen energy storage operators and electrochemical energy storage operators can dispatch excess electricity in planned scheduling based on the real-time charging and discharging volume, thereby achieving optimized scheduling of internal resources of the virtual power plant.

[0092] It can be understood that in the prior art, electrochemical energy storage operators and hydrogen energy storage operators usually participate in the master-slave game with virtual power plant operators as followers alone, that is, a master-slave game with a single leader and multiple followers is adopted. Since both parties decide on their own charging and discharging power curves, the non-cooperative game between the two parties may make it impossible for both parties to maximize their interests, or the virtual power plant operator as a whole cannot maximize its interests, that is, the master-slave game model set up has no solution. However, the present invention establishes cooperation between electrochemical energy storage operators and hydrogen energy storage operators. The alliance as a whole conducts a master-slave game with a single leader and a single follower with the virtual power plant operator through the energy storage operator, so that the decision variable of the energy storage operator participating in the game is transformed into the purchase and sale of electricity. In this way, the equilibrium solution of the game can not only meet the maximization of the interests of the virtual power plant, but also constrain the cooperative alliance established by hydrogen energy storage and electrochemical energy storage through the purchase and sale of electricity. The alliance achieves the maximum interests of both parties through energy interactive sharing and distribution of additional benefits.

[0093] In addition, if Figure 2 As shown, another embodiment of the present invention further provides a virtual power plant resource optimization scheduling system based on master-slave cooperative game, preferably using the virtual power plant resource optimization scheduling method based on master-slave cooperative game as described above, including:

[0094] A revenue objective function construction module, used to construct the revenue objective functions of virtual power plant operators, energy storage operators, hydrogen energy storage operators and electrochemical energy storage operators respectively;

[0095] A master-slave game model construction module is used to construct a master-slave game model between a virtual power plant operator and an energy storage operator based on the revenue objective function of the virtual power plant operator and the energy storage operator using a master-slave game strategy;

[0096] A cooperative game model building module is used to build a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on the revenue objective functions of hydrogen energy storage operators and electrochemical energy storage operators using cooperative game strategies;

[0097] The master-slave game model solving module is used to solve the master-slave game model with the optimization goal of maximizing the profits of the virtual power plant operator and the energy storage operator at the same time, and obtain the optimal purchase and sale price strategy of the virtual power plant operator and the optimal purchase and sale power strategy of the energy storage operator;

[0098] The cooperative game model solving module is used to solve the cooperative game model with the optimal power purchase and sales strategy of the energy storage operator as the constraint condition, the optimal power purchase and sales price strategy as the known condition, and the simultaneous maximization of the revenue of the hydrogen energy storage operator and the electrochemical energy storage operator as the optimization goal, and obtain the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator respectively;

[0099] The internal resource optimization scheduling module is used to control the charging and discharging states of each other based on the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator.

[0100] It can be understood that the virtual power plant resource optimization and scheduling system based on master-slave cooperative game in this embodiment uses the internal purchase and sale electricity price of the virtual power plant operator and the demand response of the energy storage operator as decision variables externally, and constructs a single-leader-single-follower master-slave game model with the objective function of maximizing the profits of the virtual power plant operator and the energy storage operator at the same time. Internally, a cooperative alliance of hydrogen energy storage operators and electrochemical energy storage operators is established, and through cooperative game, the optimal scheduling of internal resources is achieved with the goal of achieving the maximum interests of both parties. This can balance the distribution of interests between virtual power plant operators and internal resource providers, and improve the economic benefits of virtual power plants. At the same time, by considering the energy interaction of internal resources, it not only generates economic benefits but also avoids energy waste, which has a significant positive effect on the structural adjustment of new power systems and the construction of diversified power markets.

[0101] In addition, another embodiment of the present invention further provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and the processor executes the steps of the above method by calling the computer program stored in the memory.

[0102] In addition, another embodiment of the present invention further provides a computer-readable storage medium for storing a computer program for optimizing the scheduling of virtual power plant resources based on a master-slave cooperative game, wherein the computer program executes the steps of the method described above when running on a computer.

[0103] The general form of computer readable storage media includes: floppy disk, flexible disk, hard disk, magnetic tape, any other magnetic medium, CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with a pattern of holes, random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), flash erasable programmable read-only memory (FLASH-EPROM), any other memory chip or cartridge, or any other medium that can be read by a computer. The instructions can further be transmitted or received by a transmission medium. The term transmission medium can include any tangible or intangible medium that can be used to store, encode or carry instructions for execution by a machine, and includes digital or analog communication signals or other intangible media that facilitate the communication of the above instructions. Transmission media include coaxial cables, copper wires and optical fibers, which include the wires of a bus used to transmit a computer data signal.

[0104] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0105] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0106] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0107] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0108] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0109] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

[0110] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. 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 virtual power plant resource optimization scheduling method based on master-slave cooperative game, wherein: Energy storage operators include hydrogen energy storage operators and electrochemical energy storage operators, and are characterized by the following: Construct the revenue objective functions of virtual power plant operators, energy storage operators, hydrogen energy storage operators and electrochemical energy storage operators respectively; A master-slave game strategy is adopted to construct a master-slave game model between virtual power plant operators and energy storage operators based on their revenue objective functions. A cooperative game strategy is adopted to construct a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on their revenue objective functions. Taking the simultaneous maximization of the profits of virtual power plant operators and energy storage operators as the optimization goal, the master-slave game model is solved to obtain the optimal purchase and sale price strategy of the virtual power plant operator and the optimal purchase and sale quantity strategy of the energy storage operator; Taking the optimal power purchase and sales strategy of energy storage operators as constraints, the optimal power purchase and sales price strategy as known conditions, and the simultaneous maximization of the profits of hydrogen energy storage operators and electrochemical energy storage operators as the optimization goal, the cooperative game model is solved to obtain the optimal charging and discharging curves of hydrogen energy storage operators and electrochemical energy storage operators respectively; Based on the optimal charging and discharging curves of hydrogen energy storage operators and electrochemical energy storage operators, their respective charging and discharging states are controlled respectively.

2. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 1 is characterized in that: The profit objective function of the virtual power plant operator is: The revenue objective function of the energy storage operator is: Among them, f VPP represents the total revenue of the virtual power plant operator, f ESO represents the total revenue of the energy storage operator, represents the clearing price of the electricity market at time t, represents the electricity price sold by the virtual power plant operator to the energy storage operator at time t, represents the electricity purchase price of the virtual power plant operator from the energy storage operator at time t, represents the amount of electricity sold by the virtual power plant operator to the day-ahead power market at time t, represents the amount of electricity sold by the virtual power plant operator to the energy storage operator at time t, Represents the amount of electricity purchased by the virtual power plant operator from the energy storage operator at time t.

3. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 2 is characterized in that: The profit objective function of hydrogen energy storage operators is: The profit objective function of the electrochemical energy storage operator is: Among them, C HS represents the revenue of hydrogen energy storage operators, T represents the time period, and P MCFC,sell (t) represents the electric power sold by the fuel cell to the virtual power plant at time t, η HS Indicates the hydrogen storage efficiency of the hydrogen storage tank, S HS (t) represents the storage capacity of the hydrogen storage tank at time t, represents the input power used for the electrolyzer when the hydrogen energy storage operator purchases electricity from the virtual power plant operator at time t, represents the additional revenue allocated to hydrogen energy storage operators under the cooperative game strategy, P ELmin and P ELmax They represent the lower and upper limits of the electrolytic cell input power, respectively. It represents the input power for the electrolyzer from the excess electricity of the electrochemical energy storage operator at time t, and They represent the lower and upper limits of the hydrogen storage power of the hydrogen storage tank, P HS (t) represents the hydrogen storage power of the hydrogen storage tank at time t, and They represent the minimum and maximum effective utilization rates of the hydrogen storage tank, S HS (t) represents the storage capacity of the hydrogen storage tank at time t, Q HS Indicates the construction capacity of the hydrogen storage tank, and They represent the lower and upper limits of the fuel cell’s hydrogen input power, represents the input hydrogen power of the fuel cell at time t, P MCFC,sellmin and P MCFC,sellmax They represent the lower and upper limits of the electric power that the fuel cell can sell to the virtual power plant, P MCFC,sell (t) represents the electric power used by the fuel cell to sell electricity to the virtual power plant at time r, C storage represents the revenue of electrochemical energy storage operators, represents the discharge power of the electrochemical energy storage device sold to the virtual power plant operator at time t, E s,t represents the energy stored in the electrochemical energy storage device at time t, represents the power purchased by the electrochemical energy storage device from the virtual power plant operator at time t, represents the additional revenue allocated to the electrochemical energy storage operator under the cooperative game strategy, P char (t) represents the charging power of the electrochemical energy storage device, P dischar (t) represents the discharge power of the electrochemical energy storage device, s char and dischar Boolean variables representing the charging and discharging states of the electrochemical energy storage device, and Respectively represent the maximum charging power and maximum discharging power of the electrochemical energy storage device, SOC min and SOC max They represent the lower and upper limits of the state of charge of the electrochemical energy storage device, respectively. SOC(t) represents the state of charge of the electrochemical energy storage device at time t. s,min and E s,max Respectively represent the lower and upper limits of the capacity of electrochemical energy storage devices.

4. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 2 is characterized in that: In the master-slave game strategy, the virtual power plant operator acts as a leader and the energy storage operator acts as a follower, wherein the master-slave game model is: Among them, Ω1 represents the master-slave game model, VPP represents the virtual power plant operator, and ESO represents the energy storage operator.

5. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 3 is characterized in that: In the cooperative game strategy, hydrogen energy storage operators and electrochemical energy storage operators establish a cooperative alliance through interactive energy sharing. The alliance as a whole conducts electricity transactions with the outside world through energy storage operators. Electrochemical energy storage operators allocate idle or excess electricity to hydrogen energy storage operators, and hydrogen energy storage operators obtain additional benefits through hydrogen production and heat generation. The cooperative game model is: Among them, Ω2 represents the cooperative game model, HS represents the hydrogen energy storage operator, and cell represents the electrochemical energy storage operator.

6. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 5 is characterized in that: The optimal power purchase and sales strategy of the energy storage operator is expressed as a constraint condition: in, and They represent the optimal amount of electricity purchased and sold by the virtual power plant operator to the energy storage operator, represents the optimal power sold by the fuel cell to the virtual power plant at time t, represents the optimal discharge power of the electrochemical energy storage device to sell electricity to the virtual power plant operator at time t, represents the optimal input power for the electrolyzer when the hydrogen energy storage operator purchases electricity from the virtual power plant operator at time t, It represents the optimal power purchase of the electrochemical energy storage device from the virtual power plant operator at time t.

7. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 3 is characterized in that: The excess electricity delivered by electrochemical energy storage operators to hydrogen energy storage operators is obtained through historical data. The excess electricity is converted into thermal energy through the hydrogen boiler model and sold to the thermal load to obtain additional revenue. The additional revenue is then distributed to the hydrogen energy storage operator and the electrochemical energy storage operator using a distribution strategy based on the Shaplay value.

8. A virtual power plant resource optimization scheduling system based on master-slave cooperative game, characterized in that: include: A revenue objective function construction module, used to construct the revenue objective functions of virtual power plant operators, energy storage operators, hydrogen energy storage operators and electrochemical energy storage operators respectively; A master-slave game model construction module is used to construct a master-slave game model between a virtual power plant operator and an energy storage operator based on the revenue objective function of the virtual power plant operator and the energy storage operator using a master-slave game strategy; A cooperative game model building module is used to build a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on the revenue objective functions of hydrogen energy storage operators and electrochemical energy storage operators using cooperative game strategies; The master-slave game model solving module is used to solve the master-slave game model with the optimization goal of maximizing the profits of the virtual power plant operator and the energy storage operator at the same time, and obtain the optimal purchase and sale price strategy of the virtual power plant operator and the optimal purchase and sale power strategy of the energy storage operator; The cooperative game model solving module is used to solve the cooperative game model with the optimal power purchase and sales strategy of the energy storage operator as the constraint condition, the optimal power purchase and sales price strategy as the known condition, and the simultaneous maximization of the revenue of the hydrogen energy storage operator and the electrochemical energy storage operator as the optimization goal, and obtain the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator respectively; The internal resource optimization scheduling module is used to control the charging and discharging states of each other based on the optimal charging and discharging curves of the hydrogen energy storage operator and the electrochemical energy storage operator.

9. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and the processor executes the steps of the method according to any one of claims 1 to 7 by calling the computer program stored in the memory.

10. A computer-readable storage medium for storing a computer program for optimizing resource scheduling of a virtual power plant based on a master-slave cooperative game, characterized in that: When the computer program is run on a computer, the steps of the method according to any one of claims 1 to 7 are executed.

Images