Compressed air energy storage power station electric charge tripartite game pricing method

Abstract

The invention relates to the technical field of novel energy, in particular to a three-party game pricing method for electric charge of a compressed air energy storage power station, which comprises the following steps of: constructing a three-party game model among a power grid, a wind-solar coupled compressed air energy storage power station and a user, determining a first objective function for minimizing the operation cost of the power grid by taking the electric quantity, the electric power market price and the carbon emission cost as game variables and taking the electric power market demand and the carbon emission standard as constraint conditions; the second target function is determined according to the electricity market price, the carbon emission cost, the operation cost and the technical characteristics as constraint conditions, and the third target function is determined according to the electric charge pricing method and the self demand as constraint conditions, and the electric charge expenditure is reduced; and solving the tripartite game model by using a preset optimization algorithm to obtain an optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user.

Description

Technical Field

[0001] The present application relates to the field of new energy technologies, and in particular to a three-party game pricing method for electricity charges of compressed air energy storage power stations. Background Art

[0002] Renewable energy is considered to be one of the important means to solve the increasingly serious energy shortage and environmental pollution. However, the large-scale development and high-proportion access of renewable energy have put forward higher demands for flexible power supply, thus stimulating the development of the energy storage industry. As an important part of the power system, energy storage power stations play an important role in improving the flexibility of the power system, reducing the system operation cost and enhancing the stability of the power system. Therefore, as a key energy regulation method, energy storage power stations have received widespread attention.

[0003] At present, although the development of energy storage technology has made certain progress, there are still some major problems in its pricing mechanism. First, the pricing and operation mode of the energy storage system is relatively single, lacking diversity and flexibility, resulting in the inability to fully reflect the value of energy storage resources. Secondly, the trading mechanism of the energy storage market is not clear, lacking unified standards and specifications, which brings uncertainty and risks to market participants. In addition, due to the relatively high investment cost of battery energy storage technology, the utilization rate of the energy storage system is low, making it difficult to achieve economic benefits. Therefore, it is necessary to solve the current problem of limited application of energy storage by improving pricing and operation models, clarifying trading mechanisms, and reducing investment costs.

[0004] At present, the research on electricity pricing of energy storage power stations mainly focuses on two aspects: one is the traditional pricing method based on economic indicators such as cost and benefit, and the other is the new pricing method based on market mechanism and game theory. The traditional pricing method ignores the interaction and competition between energy storage power stations and other market participants, resulting in pricing results that may not be reasonable or cannot fully reflect the value of energy storage power stations. Therefore, the pricing mechanism based on multi-party game has become one of the current research hotspots.

[0005] However, the existing energy storage power station electricity pricing methods have problems such as insufficient comprehensive consideration of system characteristics, lack of cross-domain optimization and constraint optimization. In the context of carbon trading and demand response, the electricity pricing of wind-solar coupled compressed air energy storage power stations is crucial, and its complexity makes traditional methods unable to meet the needs. Summary of the invention

[0006] The present application provides a three-party game pricing method for the electricity charges of a compressed air energy storage power station, in order to solve the problem that the traditional pricing method ignores the interaction and competition between the energy storage power station and other market participants, resulting in that the pricing results may not be reasonable or cannot fully reflect the value of the energy storage power station.

[0007] The first aspect of the present application provides a three-party game pricing method for electricity charges of a compressed air energy storage power station, comprising the following steps: constructing a three-party game model between a power grid, a wind-solar coupled compressed air energy storage power station and a user, wherein the three-party game model is constructed by utilizing a mathematical modeling method, taking into account demand response and carbon trading, with electricity volume, electricity market price and carbon emission cost as game variables, a first objective function of minimizing the power grid operating cost determined according to the constraints of electricity market demand and carbon emission standards, a second objective function of maximizing the power station profit determined according to the constraints of electricity market price, carbon emission cost and operating cost and technical characteristics, and a third objective function of reducing electricity expenditure determined according to the electricity price pricing method and its own demand as constraints; and solving the three-party game model using a preset optimization algorithm to obtain the optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user.

[0008] Optionally, when constructing a three-party game model between the power grid, the wind-solar-coupled compressed air energy storage power station and the user, it also includes: determining the user's electricity price reward and punishment strategy based on the user's response degree based on the optimal pricing method; determining a weighted carbon emission quota reward and punishment strategy based on the carbon emissions of the wind-solar-coupled compressed air energy storage power station and the user.

[0009] Optionally, when constructing a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user, it includes: establishing a mathematical model of the wind power generation system of the energy storage power station, and based on the mathematical model of the wind power generation system, using a simulation platform to simulate the response speed and energy conversion efficiency of the wind power generation system under different landforms and wind speed conditions; establishing a mathematical model of the photovoltaic power generation system of the energy storage power station, and based on the mathematical model of the photovoltaic power generation system, using a simulation platform to simulate the response speed and energy conversion efficiency of the photovoltaic power generation system under different conditions; establishing a mathematical model of aerodynamics and thermodynamics of the energy storage power station, and based on the mathematical model of aerodynamics and thermodynamics, using a simulation platform to simulate the response speed and energy conversion efficiency of the air energy storage power station under different compression ratios and gas tank capacities; based on the simulation results of the wind power generation system, the simulation results of the photovoltaic power generation system and the simulation results of the compressed air energy storage system, using a preset mathematical optimization method to determine the optimal configuration and operation strategy of the energy storage power station.

[0010] Optionally, when constructing a three-party game model among the power grid, the wind-solar coupled compressed air energy storage power station and the user, it also includes: determining the operating cost of the wind-solar coupled compressed air energy storage power station, and evaluating the market value of the wind-solar coupled compressed air energy storage power station; determining the basic electricity price pricing of the wind-solar coupled compressed air energy storage power station based on the operating cost and the market value.

[0011] The second aspect of the present application provides a three-party game pricing system for electricity charges of compressed air energy storage power stations, including: a construction module, which is used to construct a three-party game model between a power grid, a wind-solar coupled compressed air energy storage power station and a user, wherein the three-party game model is constructed by using a mathematical modeling method, taking into account demand response and carbon trading, with electricity volume, electricity market price, and carbon emission cost as game variables, a first objective function of minimizing the operating cost of the power grid determined by the power market demand and carbon emission standards as constraints, a second objective function of maximizing the power station profit determined by the power market price, carbon emission cost, operating cost and technical characteristics as constraints, and a third objective function of reducing electricity expenditure determined by the electricity pricing method and its own demand as constraints; a pricing module, which is used to solve the three-party game model using a preset optimization algorithm to obtain the optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user.

[0012] Optionally, the construction module is also used to: determine the user's electricity price reward and punishment strategy based on the user's response degree based on the optimal pricing method; determine the weighted carbon emission quota reward and punishment strategy based on the carbon emissions of the wind-solar-coupled compressed air energy storage power station and the user.

[0013] Optionally, the construction module is also used to: establish a mathematical model of the wind power generation system of the energy storage power station, and based on the mathematical model of the wind power generation system, use a simulation platform to simulate the response speed and energy conversion efficiency of the wind power generation system under different terrain and wind speed conditions; establish a mathematical model of the photovoltaic power generation system of the energy storage power station, and based on the mathematical model of the photovoltaic power generation system, use a simulation platform to simulate the response speed and energy conversion efficiency of the photovoltaic power generation system under different conditions; establish a mathematical model of aerodynamics and thermodynamics of the energy storage power station, and based on the mathematical model of aerodynamics and thermodynamics, use a simulation platform to simulate the response speed and energy conversion efficiency of the air energy storage power station under different compression ratios and gas tank capacities; based on the simulation results of the wind power generation system, the simulation results of the photovoltaic power generation system and the simulation results of the compressed air energy storage system, use a preset mathematical optimization method to determine the optimal configuration and operation strategy of the energy storage power station.

[0014] Optionally, the building module is also used to: determine the operating cost of the wind-solar coupled compressed air energy storage power station, and evaluate the market value of the wind-solar coupled compressed air energy storage power station; determine the basic electricity price pricing of the wind-solar coupled compressed air energy storage power station based on the operating cost and the market value.

[0015] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the three-party game pricing method for electricity charges of a compressed air energy storage power station as described in the above embodiment.

[0016] The fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which is executed by a processor to implement the three-party game pricing method for electricity charges of a compressed air energy storage power station as described in the above embodiment.

[0017] In the above implementation, a three-party game model is constructed between the power grid, the wind-solar coupled compressed air energy storage power station and the user. The three-party game model is constructed by using a mathematical modeling method, considering demand response and carbon trading, with electricity, electricity market price, and carbon emission cost as game variables, and the first objective function of minimizing the power grid operation cost is determined according to the power market demand and carbon emission standards as constraints, the second objective function of maximizing the power station revenue is determined according to the power market price, carbon emission cost and operating cost and technical characteristics as constraints, and the third objective function of reducing electricity expenditure is determined according to the electricity pricing method and its own demand as constraints. The three-party game model is solved by using a preset optimization algorithm to obtain the optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user. In this way, the problem that the traditional pricing method ignores the interaction and competitive relationship between the energy storage power station and other market participants, resulting in the pricing results may not be reasonable or cannot fully reflect the value of the energy storage power station, etc., is solved. By establishing a three-party model of the power grid, the energy storage power station, and the user, the optimal pricing of the energy storage power station is achieved. The energy storage power station can flexibly adjust the electricity pricing according to the carbon emissions and demand conditions to maximize the economic and environmental benefits.

[0018] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0020] Figure 1 A flowchart of a three-party game pricing method for electricity charges of a compressed air energy storage power station provided according to an embodiment of the present application;

[0021] Figure 2 A schematic diagram of a three-party game model according to an embodiment of the present application;

[0022] Figure 3This is a schematic structural diagram of a compressed air energy storage power station according to an embodiment of the present application;

[0023] Figure 4 This is an example diagram of a three-party game pricing system for electricity charges of a compressed air energy storage power station according to an embodiment of the present application;

[0024] Figure 5 Schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0026] The following describes the three-party game pricing method for the electricity fee of the compressed air energy storage power station in the embodiment of the present application with reference to the accompanying drawings. In view of the problem that the traditional pricing method mentioned in the above background technology ignores the interaction and competitive relationship between the energy storage power station and other market participants, resulting in the pricing result may not be reasonable or cannot fully reflect the value of the energy storage power station, the present application provides a three-party game pricing method for the electricity fee of the compressed air energy storage power station, in which a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user is constructed, and the three-party game model is constructed by using a mathematical modeling method, considering demand response and carbon trading, with electricity, electricity market price, and carbon emission cost as game variables, and the first objective function of minimizing the power grid operation cost determined according to the power market demand and carbon emission standards as constraints, the second objective function of maximizing the power station revenue determined according to the power market price, carbon emission cost and operating cost and technical characteristics as constraints, and the third objective function of reducing electricity expenditure determined according to the electricity price pricing method and its own demand as constraints. The optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user is obtained by solving the three-party game model using a preset optimization algorithm. This solves the problem that the traditional pricing method ignores the interaction and competitive relationship between energy storage power stations and other market participants, resulting in unreasonable pricing results or failure to fully reflect the value of energy storage power stations. By establishing a three-party model of power grid, energy storage power station and users, the optimal pricing of energy storage power stations is achieved. Energy storage power stations can flexibly adjust electricity pricing according to carbon emissions and demand conditions to maximize economic and environmental benefits.

[0027] Specifically, Figure 1 A flow chart of a three-party game pricing method for electricity charges of a compressed air energy storage power station provided in an embodiment of the present application.

[0028] like Figure 1 As shown, the three-party game pricing method for the electricity fee of the compressed air energy storage power station includes the following steps:

[0029] In step S101, a three-party game model is constructed among the power grid, the wind-solar coupled compressed air energy storage power station and the user, wherein the three-party game model is constructed by utilizing a mathematical modeling method, taking into account demand response and carbon trading, with electricity volume, electricity market price and carbon emission cost as game variables, a first objective function of minimizing the power grid operating cost determined according to the constraints of electricity market demand and carbon emission standards, a second objective function of maximizing the power station profit determined according to the constraints of electricity market price, carbon emission cost and operating cost and technical characteristics, and a third objective function of reducing electricity expenditure determined according to the constraints of electricity pricing method and own demand.

[0030] Specifically, the interests and behaviors of each participant in the modeling electricity market need to consider the energy storage power station, the power grid and the users. The power grid is responsible for the management and operation of the electricity market, hoping to reduce energy costs while maintaining the stable operation of the power grid; the energy storage power station hopes to obtain the maximum benefits by participating in the electricity market; the user hopes to obtain a stable and reliable power supply and, if possible, the lowest electricity bill. Specifically, the preset modeling algorithm is used, demand response and carbon trading are considered, and the electricity volume, electricity market price and carbon emission cost are used as the core variables of the three-party game. Each party formulates a strategy based on the market price and carbon emission cost.

[0031] The power grid takes the power market demand and carbon emission standards as constraints to construct the first objective function of minimizing the power grid operation cost;

[0032] The energy storage power station uses the electricity market price and carbon emission costs, as well as the operating costs and technical characteristics of the energy storage power station as constraints to construct a second objective function that maximizes the power station's revenue;

[0033] Users use electricity pricing methods and their own needs to adjust electricity usage behavior and purchase decisions as constraints to construct a third objective function to reduce electricity expenditure.

[0034] Finally, a three-party game model is constructed based on the first objective function, the second objective function and the third objective function, as shown in Figure 2 Place.

[0035] Optionally, in some embodiments, when constructing a three-party game model between a power grid, a wind-solar-coupled compressed air energy storage power station and a user, it includes: establishing a mathematical model of the wind power generation system of the energy storage power station, and based on the mathematical model of the wind power generation system, using a simulation platform to simulate the response speed and energy conversion efficiency of the wind power generation system under different landforms and wind speed conditions; establishing a mathematical model of the photovoltaic power generation system of the energy storage power station, and based on the mathematical model of the photovoltaic power generation system, using a simulation platform to simulate the response speed and energy conversion efficiency of the photovoltaic power generation system under different conditions; establishing a mathematical model of aerodynamics and thermodynamics of the energy storage power station, and based on the mathematical model of aerodynamics and thermodynamics, using a simulation platform to simulate the response speed and energy conversion efficiency of the air energy storage power station under different compression ratios and gas tank capacities; based on the simulation results of the wind power generation system, the simulation results of the photovoltaic power generation system and the simulation results of the compressed air energy storage system, using a preset mathematical optimization method to determine the optimal configuration and operation strategy of the energy storage power station.

[0036] The structural diagram of the wind-solar coupled compressed air energy storage system is as follows: Figure 3 As shown, the embodiment of the present application analyzes and evaluates the performance of the wind-solar coupled compressed air energy storage system from aspects such as energy conversion efficiency, flexibility, and response speed, including the efficiency, conversion losses, etc. of wind turbines, photovoltaic modules, inverters, compressors, and expanders. The performance evaluation of the system is achieved by establishing a model on a simulation platform.

[0037] Specifically, first, a simulation model of the wind power generation system regarding fluid mechanics and mechanical transmission is established, and the energy conversion efficiency of wind power generation and the loss of wind energy in the transmission system are considered. Then, the response speed and energy conversion efficiency of the system under different landforms and wind speeds are simulated through the simulation platform.

[0038] Considering the current and voltage characteristics, light intensity, temperature influence, shadow effect and electrical loss, an overall efficiency simulation model of the photovoltaic power generation system is established, and the response speed and energy conversion efficiency of the system under different conditions are simulated and evaluated.

[0039] For the compressed air energy storage system, a simulation model involving aerodynamics and thermodynamics is established, taking into account the energy conversion efficiency of the compressor and expander, as well as the loss of air in the pipeline and gas tank. The response speed and energy conversion efficiency of the system under different compression ratios and gas tank capacities are simulated through the simulation platform.

[0040] Finally, mathematical optimization methods are used to determine the optimal system configuration and operation strategy based on the characteristics and market demand of the wind-solar coupled compressed air energy storage system. Considering factors such as system cost, efficiency, energy storage cycle, as well as demand and price fluctuations in the electricity market, decision variables such as energy storage capacity, charging and discharging rate, etc. are optimized to achieve the maximum benefit of energy storage and release. Under various constraints, the optimal system configuration and operation strategy are found to maximize system profits or electricity market benefits, so that the wind-solar coupled compressed air energy storage power station can formulate more intelligent and efficient energy storage and release strategies, and improve energy utilization and economic benefits.

[0041] Through the above method, we can fully understand the performance of the wind-solar coupled compressed air energy storage system under different operating modes, which is convenient for the operation and design of the system.

[0042] Optionally, in some embodiments, when constructing a three-party game model between a power grid, a wind-solar coupled compressed air energy storage power station and a user, it also includes: determining the operating cost of the wind-solar coupled compressed air energy storage power station, and evaluating the market value of the wind-solar coupled compressed air energy storage power station; and determining the basic electricity price pricing of the wind-solar coupled compressed air energy storage power station based on the operating cost and market value.

[0043] The equipment cost and operation and maintenance cost of the wind-solar coupled compressed air energy storage system are estimated, taking into account the costs of equipment procurement, installation, maintenance, energy consumption, etc. At the same time, its social value in improving grid stability and reducing carbon emissions can be evaluated. The cost-benefit analysis method can be used to convert social value into economic value.

[0044] At the same time, policy support is also an important factor affecting the pricing of energy storage systems. Government subsidies, tax incentives and other measures should be considered to obtain the basic electricity price of energy storage power stations to promote the development and application of clean energy technologies.

[0045] Optionally, in some embodiments, when constructing a three-party game model between a power grid, a wind-solar-coupled compressed air energy storage power station and a user, it also includes: determining a user's electricity price reward and punishment strategy based on the user's response level based on the optimal pricing method; determining a weighted carbon emission quota reward and punishment strategy based on the carbon emissions of the wind-solar-coupled compressed air energy storage power station and the user.

[0046] Specifically, the embodiment of the present application also incorporates the demand response and carbon trading mechanism of the power market into the pricing mechanism to better promote emission reduction activities. First, different electricity price mechanisms are designed for demand response, and the user's electricity price allocation strategy is determined according to the supply and demand situation of the power market and the system operation status, which encourages users to reduce electricity consumption during peak hours, thereby alleviating the pressure on power supply. At the same time, the user's demand response degree is incorporated into the pricing mechanism, and energy conservation and the balance of the power market are further promoted by rewarding users who actively participate in demand response and punishing users who do not respond.

[0047] Secondly, carbon emission quotas are set up for energy storage systems and users, and corresponding rewards or penalties are given according to their emission reduction effects. Energy storage power stations can reduce carbon emissions of power systems by flexibly adjusting energy storage and release, and obtain carbon emission quota rewards. Users can reduce carbon emissions by taking energy-saving measures or using clean energy, and obtain corresponding carbon emission quota rewards. At the same time, corresponding penalties are imposed on individuals who fail to achieve emission reduction targets to strengthen the enthusiasm and effectiveness of emission reduction behaviors. In addition, the setting of weights helps to accurately assess the impact of the subject in the overall system, thereby making the reward and penalty strategies more reasonable. For example, energy storage power stations reduce a large amount of carbon emissions through efficient energy storage and release (its emission reduction accounts for 70% of the overall emission reduction), and play a more critical role in the emission reduction process, so a higher weight (weight of 0.7) is given to the carbon emission reduction effect of energy storage power stations. Users may reduce a small amount of carbon emissions through energy-saving measures or the use of clean energy, so their contribution is relatively small, and the weight is set to 0.3. Such weight distribution will affect the final reward or penalty mechanism, thereby better motivating all parties to make reasonable adjustments in the emission reduction process.

[0048] In step S102, a preset optimization algorithm is used to solve the three-party game model to obtain the optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user.

[0049] Finally, the preset optimization algorithm is used to solve the above three-party game model to obtain the optimal pricing method for the power grid, the optimal pricing method for the energy storage power station, and the optimal pricing method for the user, so as to realize the game and coordination between the energy storage power station, the power market, and the power consumers, optimize the overall benefits of the system to the greatest extent, and achieve the balance of power supply and demand and maximize economic benefits.

[0050] According to the three-party game pricing method for the electricity fee of the compressed air energy storage power station proposed in the embodiment of the present application, a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user is constructed. The three-party game model is constructed by using a mathematical modeling method, taking into account demand response and carbon trading, with electricity, electricity market price, and carbon emission cost as game variables, and the first objective function of minimizing the power grid operation cost determined according to the power market demand and carbon emission standards as constraints, the second objective function of maximizing the power station revenue determined according to the power market price, carbon emission cost and operating cost and technical characteristics as constraints, and the third objective function of reducing electricity expenditure determined according to the electricity price pricing method and its own demand as constraints; the three-party game model is solved by using a preset optimization algorithm to obtain the optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user. Thus, the problem that the traditional pricing method ignores the interaction and competitive relationship between the energy storage power station and other market participants, resulting in the pricing results may not be reasonable or cannot fully reflect the value of the energy storage power station, etc., fully considers the influence of system characteristics and other energy technologies, and improves the adaptability and flexibility of the pricing mechanism. The introduction of demand response and carbon trading constraints has promoted the use of clean energy and the reduction of carbon emissions. Based on the three-party game model, the optimization and adjustment of the pricing mechanism have been achieved, promoting the sustainable development of the power system and the optimization of resource allocation.

[0051] Next, a three-party game pricing system for electricity charges of a compressed air energy storage power station proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0052] Figure 4 It is a block diagram of a three-party game pricing system for the electricity fee of a compressed air energy storage power station according to an embodiment of the present application.

[0053] like Figure 4 As shown, the three-party game pricing system 10 for the electricity fee of the compressed air energy storage power station includes: a construction module 100 and a pricing module 200.

[0054] Among them, the construction module 100 is used to construct a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user, wherein the three-party game model is constructed by using a mathematical modeling method, considering demand response and carbon trading, with electricity volume, electricity market price, and carbon emission cost as game variables, and the first objective function of minimizing the power grid operation cost determined by the power market demand and carbon emission standards as constraints, the second objective function of maximizing the power station profit determined by the power market price, carbon emission cost and operating cost and technical characteristics as constraints, and the third objective function of reducing electricity expenditure determined by the electricity pricing method and its own demand as constraints; the pricing module 200 is used to solve the three-party game model using a preset optimization algorithm to obtain the optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user.

[0055] Optionally, in some embodiments, building module 100 is also used to: determine the user's electricity price reward and punishment strategy based on the user's response level based on the optimal pricing method; determine the weighted carbon emission quota reward and punishment strategy based on the carbon emissions of the wind-solar-coupled compressed air energy storage power station and the user.

[0056] Optionally, in some embodiments, the construction module 100 is also used to: establish a mathematical model of the wind power generation system of the energy storage power station, and based on the mathematical model of the wind power generation system, use a simulation platform to simulate the response speed and energy conversion efficiency of the wind power generation system under different terrain and wind speed conditions; establish a mathematical model of the photovoltaic power generation system of the energy storage power station, and based on the mathematical model of the photovoltaic power generation system, use a simulation platform to simulate the response speed and energy conversion efficiency of the photovoltaic power generation system under different conditions; establish a mathematical model of aerodynamics and thermodynamics of the energy storage power station, and based on the mathematical model of aerodynamics and thermodynamics, use a simulation platform to simulate the response speed and energy conversion efficiency of the air energy storage power station under different compression ratios and gas tank capacities; based on the simulation results of the wind power generation system, the simulation results of the photovoltaic power generation system and the simulation results of the compressed air energy storage system, use a preset mathematical optimization method to determine the optimal configuration and operation strategy of the energy storage power station.

[0057] Optionally, in some embodiments, building module 100 is also used to: determine the operating cost of the wind-solar coupled compressed air energy storage power station, and evaluate the market value of the wind-solar coupled compressed air energy storage power station; determine the basic electricity price pricing of the wind-solar coupled compressed air energy storage power station based on the operating cost and market value.

[0058] It should be noted that the aforementioned explanation of the embodiment of the three-party game pricing method for the electricity fee of the compressed air energy storage power station is also applicable to the three-party game pricing system for the electricity fee of the compressed air energy storage power station of this embodiment, and will not be repeated here.

[0059] According to the three-party game pricing system of the compressed air energy storage power station electricity fee proposed in the embodiment of the present application, a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user is constructed. The three-party game model is constructed by using a mathematical modeling method, taking into account demand response and carbon trading, with electricity, electricity market price, and carbon emission cost as game variables, and the first objective function of minimizing the power grid operation cost determined according to the power market demand and carbon emission standards as constraints, the second objective function of maximizing the power station revenue determined according to the power market price, carbon emission cost, operation cost and technical characteristics as constraints, and the third objective function of reducing electricity expenditure determined according to the electricity pricing method and its own needs as constraints; the three-party game model is solved by using a preset optimization algorithm to obtain the optimal pricing method corresponding to the power grid, the wind-solar coupled compressed air energy storage power station and the user. In this way, the problem that the traditional pricing method ignores the interaction and competitive relationship between the energy storage power station and other market participants, resulting in the pricing results may not be reasonable or cannot fully reflect the value of the energy storage power station, etc., fully considers the influence of system characteristics and other energy technologies, and improves the adaptability and flexibility of the pricing mechanism. The introduction of demand response and carbon trading constraints has promoted the use of clean energy and the reduction of carbon emissions. Based on the three-party game model, the optimization and adjustment of the pricing mechanism have been achieved, promoting the sustainable development of the power system and the optimization of resource allocation.

[0060] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0061] A memory 501 , a processor 502 , and a computer program stored in the memory 501 and executable on the processor 502 .

[0062] When the processor 502 executes the program, the three-party game pricing method for the electricity fee of the compressed air energy storage power station provided in the above embodiment is implemented.

[0063] Furthermore, the electronic device further comprises:

[0064] The communication interface 503 is used for communication between the memory 501 and the processor 502 .

[0065] The memory 501 is used to store computer programs that can be executed on the processor 502 .

[0066] The memory 501 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0067] If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0068] Optionally, in a specific implementation, if the memory 501, the processor 502 and the communication interface 503 are integrated on a chip, the memory 501, the processor 502 and the communication interface 503 can communicate with each other through an internal interface.

[0069] The processor 502 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0070] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned three-party game pricing method for electricity charges of a compressed air energy storage power station.

[0071] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0072] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0073] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0074] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable storage medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable storage medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples (non-exhaustive list) of computer-readable storage media include the following: an electrical connection with one or N wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable storage medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0075] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0076] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0077] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a readable storage medium.

[0078] The computer-readable storage medium mentioned above may be a read-only memory, a disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A three-party game pricing method for electricity charges of compressed air energy storage power stations, characterized in that: The following steps are involved: Construct a three-party game model between the power grid, the wind-solar-coupled compressed air energy storage power station and the user, wherein the three-party game model is constructed by using a mathematical modeling method, taking into account demand response and carbon trading, with electricity volume, electricity market price and carbon emission cost as game variables, a first objective function of minimizing the power grid operation cost determined according to the power market demand and carbon emission standards as constraints, a second objective function of maximizing the power station revenue determined according to the power market price, carbon emission cost and operating cost and technical characteristics as constraints, and a third objective function of reducing electricity expenditure determined according to the electricity pricing method and its own demand as constraints; The three-party game model is solved using a preset optimization algorithm to obtain the optimal pricing method corresponding to the power grid, the wind-solar-coupled compressed air energy storage power station and the user.

2. The method according to claim 1, characterized in that When constructing a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user, it also includes: Determining an electricity price reward and punishment strategy for the user according to the user's response degree based on the optimal pricing method; A weighted carbon emission quota reward and punishment strategy is determined based on the carbon emissions of the wind-solar-coupled compressed air energy storage power station and the user.

3. The method according to claim 1, characterized in that When constructing a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user, it includes: Establish a mathematical model of the wind power generation system of the energy storage power station, and based on the mathematical model of the wind power generation system, use a simulation platform to simulate the response speed and energy conversion efficiency of the wind power generation system under different landforms and wind speed conditions; Establishing a mathematical model of the photovoltaic power generation system of the energy storage power station, and simulating the response speed and energy conversion efficiency of the photovoltaic power generation system under different conditions using a simulation platform based on the mathematical model of the photovoltaic power generation system; Establishing aerodynamic and thermodynamic mathematical models of the energy storage power station, and based on the aerodynamic and thermodynamic mathematical models, using a simulation platform to simulate the response speed and energy conversion efficiency of the air energy storage power station under different compression ratios and gas tank capacities; Based on the simulation results of the wind power generation system, the simulation results of the photovoltaic power generation system and the simulation results of the compressed air energy storage system, the optimal configuration and operation strategy of the energy storage power station are determined using a preset mathematical optimization method.

4. The method according to claim 1, characterized in that: When constructing a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user, it also includes: Determine the operating cost of the wind-solar coupled compressed air energy storage power station and evaluate the market value of the wind-solar coupled compressed air energy storage power station; The basic electricity price pricing of the wind-solar coupled compressed air energy storage power station is determined based on the operating cost and the market value.

5. A three-party game pricing system for electricity charges of compressed air energy storage power stations, characterized in that: include: A construction module is used to construct a three-party game model between the power grid, the wind-solar coupled compressed air energy storage power station and the user, wherein the three-party game model is constructed by using a mathematical modeling method, taking into account demand response and carbon trading, with electricity volume, electricity market price and carbon emission cost as game variables, a first objective function of minimizing the power grid operation cost determined by the power market demand and carbon emission standards as constraints, a second objective function of maximizing the power station revenue determined by the power market price, carbon emission cost and operating cost and technical characteristics as constraints, and a third objective function of reducing electricity expenditure determined by the electricity pricing method and its own demand as constraints; A pricing module is used to use a preset optimization algorithm to solve the three-party game model to obtain the optimal pricing method corresponding to the power grid, the wind-solar-coupled compressed air energy storage power station and the user.

6. The system according to claim 5, characterized in that The building blocks are also used to: Determining an electricity price reward and punishment strategy for the user according to the user's response degree based on the optimal pricing method; A weighted carbon emission quota reward and punishment strategy is determined based on the carbon emissions of the wind-solar-coupled compressed air energy storage power station and the user.

7. The system according to claim 5, characterized in that The building blocks are also used to: Establish a mathematical model of the wind power generation system of the energy storage power station, and based on the mathematical model of the wind power generation system, use a simulation platform to simulate the response speed and energy conversion efficiency of the wind power generation system under different landforms and wind speed conditions; Establishing a mathematical model of the photovoltaic power generation system of the energy storage power station, and simulating the response speed and energy conversion efficiency of the photovoltaic power generation system under different conditions using a simulation platform based on the mathematical model of the photovoltaic power generation system; Establishing aerodynamic and thermodynamic mathematical models of the energy storage power station, and based on the aerodynamic and thermodynamic mathematical models, using a simulation platform to simulate the response speed and energy conversion efficiency of the air energy storage power station under different compression ratios and gas tank capacities; Based on the simulation results of the wind power generation system, the simulation results of the photovoltaic power generation system and the simulation results of the compressed air energy storage system, the optimal configuration and operation strategy of the energy storage power station are determined using a preset mathematical optimization method.

8. The system according to claim 5, characterized in that The building blocks are also used to: Determine the operating cost of the wind-solar coupled compressed air energy storage power station and evaluate the market value of the wind-solar coupled compressed air energy storage power station; The basic electricity price pricing of the wind-solar coupled compressed air energy storage power station is determined based on the operating cost and the market value.

9. An electronic device, characterized in that: It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a three-party game pricing method for electricity charges of a compressed air energy storage power station as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement a three-party game pricing method for electricity charges of a compressed air energy storage power station as described in any one of claims 1-4.

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