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

Abstract

The application discloses a virtual power plant resource optimization scheduling method and system based on master-slave cooperative game, which takes the internal purchase and sale price of the virtual power plant operator and the demand response of the energy storage operator as the decision variable outside, constructs a single leader-single follower master-slave game model with the maximum of the virtual power plant operator and the energy storage operator income as the objective function, and establishes a cooperation alliance of the hydrogen energy storage operator and the electrochemical energy storage operator inside, so that the maximum benefit of the cooperation parties is taken as the target through the cooperative game, the internal resource optimization scheduling is realized, the benefit distribution of the virtual power plant operator and the internal resource operator can be balanced, the economic benefit of the virtual power plant is improved, the energy interaction of the internal resource is considered, economic benefits are generated, energy waste is avoided, and the structure adjustment of the new power system and the construction of the diversified power market have a significant positive effect.

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 a master-slave cooperative game, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the rapid development of distributed energy resources (DEGs), such as distributed power generation (DGs), energy storage, and controllable loads, the construction of new power systems presents significant challenges. DEGs are characterized by small capacity, diverse resource types, large numbers, and geographical dispersion, as well as their ability to regulate. Rationally and effectively dispatching DEGs to provide auxiliary power services for the grid is crucial. To achieve coordinated control and energy management of these distributed resources, virtual power plants (VPPs) are emerging as a novel approach to aggregate control of a large number of DEGs. Through advanced communication technologies and control strategies, VPPs aggregate distributed resources such as photovoltaics, wind power, energy storage, electric vehicles, and user loads to participate in power market ancillary services or load demand response, achieving grid peak and frequency regulation. When participating in power market ancillary services, VPPs typically implement refined control and dispatch of aggregated loads through economic dispatch. Based on electricity price forecasts, load forecasts, power output forecasts, and the basic information and constraints of each DEG within the VPP, VPPs comprehensively analyze information from the day-ahead energy market and the DEGs within the VPP to optimize dispatch decisions and formulate economic dispatch plans. These VPPs interact with the day-ahead energy market externally and coordinate dispatch of DEGs internally.

[0003] However, existing scheduling methods primarily focus on how VPPs, as influencers of market electricity prices, can maximize their own operational profits through reasonable economic scheduling. This neglects how VPPs, as price setters for aggregated energy owners, can achieve optimal internal scheduling within aggregated energy operators, thereby maximizing their economic benefits. Therefore, there is an urgent need to provide diverse scheduling strategies within virtual power plants and aggregated energy, thereby achieving a win-win situation for both 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, and 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 method for optimizing and scheduling virtual power plant resources based on a master-slave cooperative game is provided, wherein energy storage operators include hydrogen energy storage operators and electrochemical energy storage operators, and the method includes the following:

[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] With the optimization goal of maximizing the profits of both the virtual power plant operator and the energy storage operator, a master-slave game model is solved to obtain the optimal electricity purchase and sales price strategy for the virtual power plant operator and the optimal electricity purchase and sales strategy for the energy storage operator.

[0010] Using the energy storage operator's optimal electricity purchase and sales strategy as a constraint, the optimal electricity purchase and sales price strategy as a known condition, and the simultaneous maximization of the revenue of hydrogen energy storage operators and electrochemical energy storage operators as the optimization goal, a cooperative game model was solved to obtain the optimal charge and discharge curves for hydrogen energy storage operators and electrochemical energy storage operators, respectively.

[0011] Based on the optimal charge and discharge curves of hydrogen energy storage operators and electrochemical energy storage operators, their respective charge and discharge states are controlled separately.

[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 that the virtual power plant operator purchases 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.

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

[0018]

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

[0020]

[0021] Among them, C HS represents the profit 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 of the electrolyzer used by the hydrogen energy storage operator when purchasing 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, It represents the input power of 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 hydrogen storage tanks, 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 of the fuel cell used 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 s 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 electrochemical energy storage devices, SOC min and SOC max They represent the lower and upper limits of the state of charge of the electrochemical energy storage device, SOC(t) represents the state of charge of the electrochemical energy storage device at time t, and E s,min and E s,max They represent the lower and upper limits of the capacity of electrochemical energy storage devices, respectively.

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

[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 as follows:

[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, historical data is used to calculate the excess electricity delivered by electrochemical energy storage operators to hydrogen energy storage operators. The excess electricity is converted into thermal energy through the hydrogen boiler model and then 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, comprising:

[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 virtual power plant operators and energy storage operators based on their revenue objective functions using a master-slave game strategy;

[0035] A cooperative game model construction module is used to construct a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on their revenue objective functions using a cooperative game strategy;

[0036] The master-slave game model solving module is used to solve the master-slave game model with the optimization goal of maximizing the revenue of both the virtual power plant operator and the energy storage operator, 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 using the energy storage operator's optimal power purchase and sales strategy as a constraint, the optimal power purchase and sales price strategy as a 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, to obtain the optimal charge and discharge curves for 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 status of each hydrogen energy storage operator and electrochemical energy storage operator based on their optimal charging and discharging curves.

[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 is configured to execute 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, and 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. Internally, by establishing a cooperative alliance of hydrogen energy storage operators and electrochemical energy storage operators, 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 objects, features and advantages, the present invention has other objects, features and advantages. The present invention will be further described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying 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 of the embodiments in this 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 operators include hydrogen energy storage operators and electrochemical energy storage operators, 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, a master-slave game model is constructed between the virtual power plant operator and the energy storage operator based on their revenue objective functions.

[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 revenue 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 quantity strategy of the energy storage operator;

[0054] Step S5: Using the energy storage operator's optimal power purchase and sales strategy as a constraint, the optimal power purchase and sales price strategy as a known condition, and maximizing the revenue of both 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 charge and discharge curves for the hydrogen energy storage operator and the electrochemical energy storage operator, respectively.

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

[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, by establishing a cooperative alliance of hydrogen energy storage operators and electrochemical energy storage operators, 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.

[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, as an influencer of market prices, submit the bid price and bid power in the day-ahead market to the electricity market. Through bidding decisions, it will influence the spot market clearing price and decide the internal purchase and sale price of electricity for the energy storage operator based on the market clearing price to maximize the total operating profit 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 that the virtual power plant operator purchases 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] A hydrogen storage operator's hydrogen storage power generation system consists of four components: an electrolyzer hydrogen production system, a hydrogen storage tank system, a fuel cell hydrogen power generation system, and a hydrogen boiler heating system. The hydrogen storage power generation system operates as follows: first, it meets its own load demand. Excess electricity is produced by electrolyzing water to produce hydrogen, which is stored in hydrogen storage tanks to provide energy storage for the system. When electricity is needed, the hydrogen is converted into electricity using fuel cells or other conversion methods for self-use or grid trading. During periods of low electricity demand, hydrogen can also be converted into heat energy through hydrogen boilers to supply thermal loads. Due to a cooperative game mechanism, hydrogen storage can not only purchase and sell electricity from virtual power plants as part of an energy storage operator alliance, but also receive idle or excess electricity from electrochemical energy storage providers, generating additional revenue by converting it into hydrogen. The operating mechanism of an electrochemical energy storage operator involves first meeting its own load demand. When the virtual power plant's electricity purchase price is low, the electrochemical energy storage operator purchases electricity from the virtual power plant operator for charging. When the virtual power plant's electricity sales price is high, the electrochemical energy storage operator discharges electricity and sells it 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 of 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 electric 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 hydrogen rate 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 The hydrogen boiler's heating efficiency. When the hydrogen energy storage power generation system meets the electricity load demand or is in a 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 heat supply and demand balance and 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 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 electricity sold to the virtual power plant:

[0068] The electrochemical energy storage equipment of electrochemical energy storage operators is lithium-ion batteries, and the output model of lithium-ion batteries 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, Respectively 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 Represents 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 used to prevent the energy storage device from charging and discharging simultaneously 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 hydrogen energy storage operators can be expressed as:

[0070]

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

[0072]

[0073] Among them, C HS represents the profit 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 of the electrolyzer used by the hydrogen energy storage operator when purchasing 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, It represents the input power of 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 hydrogen storage tanks, 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 of the fuel cell used 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 s 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 electrochemical energy storage devices, SOC min and SOC max They represent the lower and upper limits of the state of charge of the electrochemical energy storage device, SOC(t) represents the state of charge of the electrochemical energy storage device at time t, and E s,min and E s,max They represent the lower and upper limits of the capacity of electrochemical energy storage devices, respectively.

[0074] It can be understood that in a master-slave game strategy, the virtual power plant operator serves as the leader and the energy storage operator as the follower. Specifically, the leader is the virtual power plant operator, with its revenue maximization as its objective function. It determines the optimal internal purchase and sale price of electricity by combining the market clearing price and energy storage electricity demand to maximize its profits. The follower is the energy storage operator, with its revenue maximization as its objective function. It responds to the demand based on the purchase and sale price signal determined by the virtual power plant operator and determines its own purchase and sale amount to maximize its profits. At the same time, the demand response determined by the energy storage operator will affect the virtual power plant operator's profits, thus forming a master-slave game strategy with a single leader and a single follower. In the master-slave game, 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 interest equilibrium solution appears, that is, both parties are concentrated on one point and this point maximizes the interests of all participants. This can end the game process and output the optimal game solution.

[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 both 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] Understandably, a cooperative game strategy involves energy storage operators forming a cooperative alliance, dispatching only charging and discharging capacity from different energy storage providers, specifically hydrogen and electrochemical storage. Without a cooperative alliance, hydrogen storage is expensive to build, and its power generation costs far exceed those of electrochemical storage. Simply participating in the master-slave game as a follower would be unable to compete with other followers. Furthermore, the energy storage equipment clustered in a virtual power plant is often idle. If the batteries are not discharged promptly after charging, the lithium battery capacity will decay over time. Therefore, both hydrogen and electrochemical storage operators aim to maximize their own profits while maximizing overall returns. Therefore, in a cooperative game strategy, hydrogen and electrochemical storage operators establish a cooperative alliance through energy sharing. The alliance trades electricity through the energy storage operators, with electrochemical storage operators allocating idle or excess power to hydrogen storage operators. Hydrogen storage operators then earn additional revenue through hydrogen and heat production, thereby fully enhancing the flexibility and economic efficiency of energy storage system operations.

[0079] The cooperative game model mainly includes three elements: participants, strategies, and benefits. The participants in the cooperative game refer to the entities that make decisions in the cooperative game, which are hydrogen energy storage operators and electrochemical energy storage operators, and 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 Let the strategy set of electrochemical energy storage be 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] As can be understood, with the optimization goal of maximizing the revenue of both the virtual power plant operator and the energy storage operator, a differential algorithm is employed to solve the master-slave game model, resulting in the optimal electricity purchase and sales price strategy for the virtual power plant operator and the optimal electricity purchase and sales strategy for the energy storage operator. The differential algorithm primarily solves nonlinear optimization problems, offering a limited number of control parameters and high convergence efficiency. This is an existing algorithm, and the detailed solution process is omitted here. As an example, the simplified solution process is as follows: first input data and parameters, and take the day-ahead clearing electricity price in the electricity market as a known quantity. 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 use the constraint conditions as parameter boundary restrictions; then, the virtual power plant operator provides the energy storage operator with purchase and sale price information, and the lower-level energy storage operator makes its own demand response, that is, the electricity demand signal, based on the initial 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 iteration, it is determined whether the algorithm has reached the number of iterations. If the number of game games has not been reached, the above process is repeated. If the difference is less than the model accuracy, it is the 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, which enables the energy storage operator to spontaneously adjust its own charging and discharging time and charging and discharging amount according to the electricity price signal, and finally outputs the optimal charging and discharging amount as follows:

[0085] It is understandable 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 must be used 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, with the energy storage operator's optimal electricity purchase and sales strategy as a constraint, the optimal electricity purchase and sales price strategy as a known condition, and the simultaneous maximization of the profits of hydrogen energy storage operators and electrochemical energy storage operators as the optimization goal, a particle swarm optimization algorithm is used to solve the cooperative game model to obtain the optimal charging and discharging curves of hydrogen energy storage operators and electrochemical energy storage operators. 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 as 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 stopping 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, Finally, the optimal charge and discharge status of hydrogen energy storage operators and electrochemical energy storage operators is controlled according to the optimal charge and discharge curves, achieving optimal dispatching commands for the internal resources of energy storage operators.

[0091] In addition, considering that in actual scheduling, 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 charge and discharge 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. Converted into heat energy through the hydrogen boiler model, and then sold to heat loads to obtain additional income Then, 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 schedule excess electricity in planned scheduling based on the real-time charging and discharging volume, thereby achieving optimized scheduling of internal resources in 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 charge and discharge 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 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 single-leader-single-follower master-slave game with the virtual power plant operator through the energy storage operator, so that the decision variable for the energy storage operator to participate in the game is converted to 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 maximum interests of both parties are achieved through the interactive sharing of energy and the distribution of additional benefits within the alliance.

[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 virtual power plant operators and energy storage operators based on their revenue objective functions using a master-slave game strategy;

[0096] A cooperative game model construction module is used to construct a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on their revenue objective functions using a cooperative game strategy;

[0097] The master-slave game model solving module is used to solve the master-slave game model with the optimization goal of maximizing the revenue of both the virtual power plant operator and the energy storage operator, 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 using the energy storage operator's optimal power purchase and sales strategy as a constraint, the optimal power purchase and sales price strategy as a 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, to obtain the optimal charge and discharge curves for 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 status of each hydrogen energy storage operator and electrochemical energy storage operator based on their optimal charging and discharging curves.

[0100] It can be understood that the virtual power plant resource optimization and scheduling system based on the master-slave cooperative game in this embodiment uses the internal purchase and sale electricity prices 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, by establishing a cooperative alliance of hydrogen energy storage operators and electrochemical energy storage operators, 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.

[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 is configured to execute the steps of the above method by calling the computer program stored in the memory.

[0102] In addition, another embodiment of 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.

[0103] Common computer-readable storage media include: floppy disks, flexible disks, hard disks, magnetic tape, any other magnetic media, CD-ROMs, any other optical media, 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. Instructions can further be transmitted or received via a transmission medium. The term transmission medium may 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 communication of such instructions. Transmission media include coaxial cables, copper wire, and fiber optics, including 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 application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the 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 embodiment of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal translation 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 produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. 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 that can direct a computer or other programmable data processing device to work 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 The 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 operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0108] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional 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 that fall within the scope of the present application.

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

[0110] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection 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. With the optimization goal of maximizing the profits of both the virtual power plant operator and the energy storage operator, a master-slave game model is solved to obtain the optimal electricity purchase and sales price strategy for the virtual power plant operator and the optimal electricity purchase and sales strategy for the energy storage operator. Using the energy storage operator's optimal electricity purchase and sales strategy as a constraint, the optimal electricity purchase and sales price strategy as a known condition, and the simultaneous maximization of the revenue of hydrogen energy storage operators and electrochemical energy storage operators as the optimization goal, a cooperative game model was solved to obtain the optimal charge and discharge curves for hydrogen energy storage operators and electrochemical energy storage operators, respectively. Based on the optimal charge and discharge curves of hydrogen energy storage operators and electrochemical energy storage operators, the respective charge and discharge states are controlled; 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 that the virtual power plant operator purchases 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; The profit objective function of hydrogen energy storage operators is: The profit objective function of electrochemical energy storage operators is: Among them, C HS represents the profit 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 of the electrolyzer used by the hydrogen energy storage operator when purchasing 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, It represents the input power of 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 hydrogen storage tanks, 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 of the fuel cell used 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 s 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 electrochemical energy storage devices, SOC min and SOC max They represent the lower and upper limits of the state of charge of the electrochemical energy storage device, SOC(t) represents the state of charge of the electrochemical energy storage device at time t, and E s,min and E s,max They represent the lower and upper limits of the capacity of electrochemical energy storage devices, respectively.

2. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 1 is characterized in that: In the master-slave game strategy, the virtual power plant operator acts as the leader and the energy storage operator acts as the follower. 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.

3. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 1 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 external parties 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 revenue through hydrogen production and heat generation. The cooperative game model is as follows: Among them, Ω2 represents the cooperative game model, HS represents the hydrogen energy storage operator, and cell represents the electrochemical energy storage operator.

4. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 3 is characterized in that: The optimal power purchase and sales strategy of the energy storage operator is expressed as a constraint condition as follows: 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.

5. The virtual power plant resource optimization scheduling method based on master-slave cooperative game according to claim 1 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 then 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 an allocation strategy based on the Shaplay value.

6. A virtual power plant resource optimization scheduling system based on master-slave cooperative game, adopting the virtual power plant resource optimization scheduling method based on master-slave cooperative game according to any one of claims 1 to 5, 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 virtual power plant operators and energy storage operators based on their revenue objective functions using a master-slave game strategy; A cooperative game model construction module is used to construct a cooperative game model between hydrogen energy storage operators and electrochemical energy storage operators based on their revenue objective functions using a cooperative game strategy; The master-slave game model solving module is used to solve the master-slave game model with the optimization goal of maximizing the revenue of both the virtual power plant operator and the energy storage operator, 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 using the energy storage operator's optimal power purchase and sales strategy as a constraint, the optimal power purchase and sales price strategy as a 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, to obtain the optimal charge and discharge curves for 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 status of each hydrogen energy storage operator and electrochemical energy storage operator based on their optimal charging and discharging curves.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and the processor is configured to execute the steps of the method according to any one of claims 1 to 5 by calling the computer program stored in the memory.

8. 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 5 are executed.

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