Energy storage cost dissipation evolutionary game method

Abstract

The application relates to a kind of energy storage cost dredging evolutionary game method, comprising: (1) collecting the corresponding information of target area power supply side, grid side, user side main body, and establishing the evolutionary game matrix for energy storage cost dredging;(2) based on the evolutionary game matrix, calculate the expected income of power supply side main body strategy selection and its replication dynamic equation;(3) based on the evolutionary game matrix, calculate the expected income of grid side main body strategy selection and its replication dynamic equation;(4) based on the evolutionary game matrix, calculate the expected income of user side main body strategy selection and its replication dynamic equation;(5) carry out evolutionary game, analyze the scene of evolutionary game;(6) combined with the policy that may be taken for the result of each evolutionary game, consider the change of user demand response willingness, simulate the probability change of user willingness by Markov chain, and return to step (1) to continue evolutionary game.The method is beneficial to accurately analyze the possibility of each main body bearing energy storage cost.

Description

Technical Field

[0001] This invention relates to a cost-distribution chemical game method for energy storage. Background Technology

[0002] In the current technological landscape, the construction of new power systems based primarily on new energy sources has developed rapidly. However, in reality, the rapid expansion of new energy installed capacity has led to a "deficit" in supporting infrastructure to ensure the stability of new energy sources, and the gap in peak-shaving resources has gradually widened, resulting in a sharp decline in the utilization rate of new energy sources and an increase in wind and solar curtailment. To ensure the stable operation of the power grid, sufficient peak-shaving resources are needed to fill the gap. Due to their inherent characteristics, thermal power units cannot provide stable peak-shaving uplink and downlink reserve capacity. Therefore, new energy storage, with its advantages of fast response speed, short construction period, and less constraint on development scale due to resource conditions, has been given an extremely important strategic position. However, the operating mechanism of new energy storage is still under exploration, so it is necessary to consider how to construct an energy storage operating model. Summary of the Invention

[0003] The purpose of this invention is to provide a deductive game theory method for energy storage cost derivation, which is beneficial for accurately analyzing the probability of each entity bearing the energy storage cost.

[0004] To achieve the above objectives, the technical solution adopted by this invention is: a cost-based energy storage evolutionary game method, comprising the following steps:

[0005] (1) Collect relevant information on the main entities on the power supply side, grid side, and user side in the target area, and establish an evolutionary game matrix for energy storage cost diversion;

[0006] (2) Based on the evolutionary game matrix, calculate the expected payoff of the power supply side subject's strategy selection and its replication dynamic equation;

[0007] (3) Based on the evolutionary game matrix, calculate the expected returns of the main strategy selection of the power grid side and its replication dynamic equation;

[0008] (4) Based on the evolutionary game matrix, calculate the expected payoff of the user-side subject's strategy selection and its replication dynamic equation;

[0009] (5) Conduct evolutionary game theory and analyze the evolutionary game scenario;

[0010] (6) Considering the changes in user willingness to respond to the policy that may be adopted in response to the outcome of each evolutionary game, a Markov chain is used to simulate the changes in user willingness probability, and then return to step (1) to continue the evolutionary game.

[0011] Furthermore, in step (1), the evolutionary game matrix is ​​established as follows:

[0012]

[0013] Among them, Z a Z b Z c Each represents a different strategy combination. n ×b n ×c n The benefits to the power supply side, the grid side, and the load side under (n=1∪n=2).

[0014] Furthermore, under the combination of power source side purchasing energy storage capacity, grid side purchasing energy storage capacity, and user side demand response strategies, the benefits for the power source side, grid side, and load side are as follows:

[0015]

[0016] Under the combined strategy of purchasing energy storage capacity on the power generation side, purchasing energy storage capacity on the grid side, and no demand response on the user side, the benefits to the power generation side, grid side, and load side are as follows:

[0017] (Z a ) a1，b1，c2 =Q a1 (P a1 -C a )+α1(Q a -Q a1 (P) a1 -C b1 )+(1-α1)(Q a -Q a1 (P) a1 -C a )

[0018] (Z b ) a1，b1，c2 =Q a1 (P b -P a1 )+α1(Q a -Q a1 (P) b -P a1 )+(1-α1)(Q a -Q a1 (P) b -C b2 )

[0019] (Z c ) a1，b1，c2 =BQ a P b

[0020] Under the combined strategy of the power generation side purchasing energy storage capacity, the grid side not purchasing energy storage capacity, and the user side demand response strategy, the benefits to the power generation side, the grid side, and the load side are as follows:

[0021] (Z a ) a1，b2，c1 =(Q a1 (P a1 -C a )+α1(Q a -Q a1 (P) a1 -C b1 )+(1-α1)(Q a -Q a1 (P) a1 -C a )

[0022] (Z b ) a1，b2，c1 =Q a1 (P b -P a1 )+α1(Q a -Q a1 (P) b -P a1 )+(1-α1)(Q a -Q a1 (P) a1 -C b3 )

[0023] (Z c ) a1，b2，c1 =BQ a P b +(1-α1)(Q a -Q a1 C b3 )

[0024] Under the strategy combination of the power generation side purchasing energy storage capacity, the grid side not purchasing energy storage capacity, and the user side not demand response, the benefits to the power generation side, the grid side, and the load side are as follows:

[0025] (Z a ) a1，b2，c2 =Q a1 (P a1 -C a )+(Q a -Q a1 (P) a1 -C b1 )

[0026] (Z b ) a1，b2，c2 =Q a1 (P b -P a1 )+(Q a -Q a1 (P) b -P a1)

[0027] (Z c ) a1，b2，c2 =BQ a P b

[0028] Under a combination of strategies involving no energy storage purchases by the power generation side, energy storage purchases by the grid side, and demand response by the user side, the benefits for the power generation side, grid side, and load side are as follows:

[0029] (Z a ) a2，b1，c1 =(Q a (P a1 -C a )-β

[0030] (Z b ) a2，b1，c1 =Q a (P b -P a1 )-α2(Q a -Q a1 C b2 -(1-α2)(Q a -Q a1 C b3 +β

[0031] (Z c ) a2，b1，c1 =BQ a P b +(1-α2)(Q a -Q a1 C b3 )

[0032] Under the combined strategy of no energy storage capacity purchase by the power generation side, energy storage capacity purchase by the grid side, and no demand response by the user side, the benefits to the power generation side, grid side, and load side are as follows:

[0033] (Z a Z b Z c ) a2，b1，c2 =(Q a (P a1 -C a )-β,Q a (P b -P a1 )-(Q a -Q a1 C b2 +β,BQ a P b )

[0034] Under a combination of power generation and grid-side energy storage capacity not being purchased, and user-side demand response strategies, the benefits to the power generation, grid, and load sides are as follows:

[0035] (Z a Z b Z c ) a2，b2，c1 =(Q a (P a1 -C a )-β,Q a (P b -P a1 )-(Q a -Q a1 C b3 +β,BQ a P b +(Q a -Q a1 C b3 )

[0036] Under a strategy combination where the power supply side does not purchase energy storage capacity, the grid side does not purchase energy storage capacity, and the user side does not require demand response, the benefits to the power supply side, the grid side, and the load side are as follows:

[0037] (Z a Z b Z c ) a2，b2，c2 =(Q a1 (P a1 -C a )-β,Q a1 (P b -P a1 )+β,B-B1-Q a1 P b )

[0038] Among them, P a1 The grid connection price per unit of electricity generated on the power supply side; P b Electricity price per unit of electricity purchased by the user; Q a Q represents the total power generation planned for trading on the power supply side. a1 α1 represents the maximum available power generation on the power source side without purchasing energy storage capacity; α2 represents the proportion of power output compensated by power source-side energy storage when supply and demand are unbalanced; C represents the proportion of power output compensated by grid-side energy storage or inter-regional power transmission when supply and demand are unbalanced. a The levelized cost of electricity (LCOE) for power supply without the application of flexible resources; C b1 The levelized cost of electricity (LCOE) for power-side application of flexible resources; C b2 The levelized cost of electricity (LCOE) for grid-side application of flexible resources; C b3β is the cost of demand response for load-side applications; B is the penalty paid for failure to supply power as contracted due to the power supply side not using flexible resources; B is the benefit gained from normal production on the load side; B1 is the benefit lost due to abnormal production on the load side.

[0039] Furthermore, in step (2), the expected return U of the power supply entity choosing to purchase energy storage capacity versus not purchasing energy storage capacity is... a1 U a2 They are respectively:

[0040] Ua1=y[z(Za) a1，b1，c1 +(1-z)(Za) a1，b1，c2 ]+(1-y)[z(Za) a1，b2，c1 +(1-z)(Za) a1，b2，c2 ]

[0041] Ua2=y[z(Za) a2，b1，c1 +(1-z)(Za) a2，b1，c2 ]+(1-y)[z(Za) a2，b2，c1 +(1-z)(Za) a2，b2，c2 ]

[0042] The dynamic equation for the strategy of whether the power supply entity purchases energy storage capacity is:

[0043]

[0044] Furthermore, in step (3), the expected revenue U of the grid-side entity choosing to purchase energy storage capacity versus not purchasing energy storage capacity is... b1 U b2 They are respectively:

[0045] U b1 =x[z(Z) b ) a1，b1，c1 +(1-z)(Z b ) a1，b1，c2 ]+(1-x)[z(Z b ) a2，b1，c1 +(1-z)(Z b ) a2，b1，c2 ]

[0046] U b2 =x[z(Z) b ) a1，b2，c1 +(1-z)(Z b ) a1，b2，c2 ]+(1-x)[z(Z b ) a2，b2，c1 +(1-z)(Z b ) a2，b2，c2 ]

[0047] The dynamic equation for the strategy of whether the grid-side entity should purchase energy storage capacity is:

[0048]

[0049] Furthermore, in step (4), the expected benefit U of the user-side subject choosing to respond to the demand and reject the demand response is... c1 U c2 They are respectively:

[0050] U c1 =x[y(Z) c ) a1，b1，c1 +(1-y)(Z c ) a1，b2，c1 ]+(1-x)[y(Z c ) a2，b1，c1 +(1-y)(Z c ) a2，b2，c1 ]

[0051] U c2 =x[y(Z) c ) a1，b1，c2 +(1-y)(Z c ) a1，b2，c2 ]+(1-x)[y(Z c ) a2，b1，c2 +(1-y)(Z c ) a2，b2，c2 ]

[0052] The strategy for whether the user-side entity uses energy storage technology is replicated using the dynamic equation:

[0053]

[0054] Furthermore, in step (6), considering the changes in users' willingness to respond to demands based on the possible policies adopted for each evolutionary game outcome, after implementing the corresponding policies, the probability of users favoring demand response or not demand response is obtained; a state space {1,2} is established, where state 1 represents demand response and state 2 represents not demand response; during the survey, the demand response remains unchanged, denoted as p. 11 The transformation from a demand response to a rejection is denoted as p. 12 Correspondingly, the rejection of demand response and the transformation into demand response is denoted as p. 21 If the original attitude is not changed, it is recorded as p. 22 Based on this, a one-step transition probability matrix is ​​constructed.

[0055]

[0056] Considering that the user demand response only takes into account the current state, it can be understood as a process without aftereffects, and is regarded as an irreducible, aperiodic Markov process. This discrete Markov chain is considered to be an ergodic state. Based on this, the probability of the user demand response is updated using the following formula:

[0057]

[0058] The Markov chain is used to simulate the change in user willingness probability, and then the game is continued by returning to step (1).

[0059] Compared with existing technologies, the present invention has the following beneficial effects: The present invention provides an evolutionary game theory method for alleviating energy storage costs, which improves the energy storage cost alleviation method. It uses an evolutionary game theory approach to analyze the final bearer of energy storage costs and considers the impact of measures taken after each evolutionary game on the user's demand response attitude. It uses discrete Markov chains for simulation, and ensures the effectiveness of Markov chain transfer effects by ensuring the authenticity of survey data. It also ensures the reliability of the evolutionary game theory method by iterating on the user-side probabilities, thereby achieving more accurate game results and making the bearer of energy storage costs more reasonable. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating the method implementation of an embodiment of the present invention. Detailed Implementation

[0061] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0062] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of this application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0063] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0064] All capacity costs are channeled through capacity sales, and the three parties involved in the game—the power supply side, the grid side, and the user side—are boundedly rational. Each party's strategy choices gradually stabilize to the optimal strategy over time based on changes in environmental conditions.

[0065] This invention provides a cost-sharing strategy game for energy storage. Following the principle of "who benefits, who bears," energy storage power stations primarily sell capacity to power generation plants and grid operators. The strategy space of the power generation side is A = (a1, a2) = (purchase energy storage capacity, do not purchase energy storage capacity), choosing a1 with probability x and a2 with probability (1-x), where x∈[0,1]. The strategy space of the grid side is B = (b1, b2) = (purchase energy storage capacity, do not purchase energy storage capacity), choosing b1 with probability y and b2 with probability (1-y), where y∈[0,1]. The strategy space of the user side is C = (c1, c2) = (respond to demand, do not respond to demand), choosing c1 with probability z and c2 with probability (1-z), where z∈[0,1].

[0066] The strategic choices of different stakeholders will affect the revenues of other stakeholders, thus causing the strategic selection process to evolve dynamically. To ensure the safe operation of the new power system, the revenue of power generation entities will be divided into three parts: revenue from power generation unrelated to energy storage technology, revenue from power generation consumed using energy storage technology, and revenue from power generation consumed by the grid and user-side flexibility resources. Furthermore, when a power generation entity refuses to purchase energy storage capacity, it will be required to pay a penalty to the grid side for failing to provide the corresponding electricity as contracted. The revenue of the grid side entities comes from transmission revenue, including power generation unrelated to energy storage technology and additional power generation consumed due to the purchase of energy storage capacity. In addition, when the user side adopts a demand response strategy, the grid side needs to pay the user side certain costs. The user side is the electricity demander, purchasing electricity from the grid side for economic production activities. During normal production activities using electricity, they can obtain revenue B, but when the power system supply is insufficient, a loss B1 will occur. Furthermore, when choosing to utilize energy storage technology to implement a demand response strategy, they can obtain revenue provided by the grid side.

[0067] like Figure 1 As shown, the energy storage cost decentralization evolutionary game method provided in this embodiment includes the following steps:

[0068] (1) Collect relevant information on the power supply side, grid side and user side of the target area, and establish an evolutionary game matrix for energy storage cost diversion based on the assumptions of the method.

[0069] In this embodiment, historical operational data of an energy storage project in a certain province is used as the basis for evolutionary simulation to explore new cost-sharing pathways for energy storage. It is assumed that under a unified price clearing market model, the annual power generation of the main power source is 7.9 × 10⁻⁶. 8 MWh, when faced with uncertainties, requires the consumption of 1.42 × 10 8The MWh of flexible resources. The market electricity price that year was 405 yuan / MWh, and the transmission and distribution price was 100 yuan / MWh. The energy storage technology on the power generation side was electrochemical energy storage, with a levelized cost of approximately 440 yuan / MWh; the energy storage technology invested in on the grid side was also electrochemical energy storage, with a levelized cost of 310 yuan / MWh. Assuming the operating cost of power generation on the power generation side is 350 yuan / MWh, then the cost of power generation combined with energy storage on the power generation side is 790 yuan / MWh. To facilitate simulation, the initial parameter values ​​can be appropriately reduced and adjusted. The initial parameters are shown in Table 1.

[0070] Table 1 Initial settings for each parameter

[0071] parameter <![CDATA[P a1 ]]> <![CDATA[P b ]]> <![CDATA[Q a ]]> <![CDATA[Q a1 ]]> <![CDATA[α1]]> <![CDATA[α2]]> <![CDATA[C a ]]> numerical values 4 5 7.9 1.42 0.8 0.1 3.5 parameter <![CDATA[C b1 ]]> <![CDATA[C b2 ]]> <![CDATA[C b3 ]]> β B B1 numerical values 7.9 3.1 1 0 5 1

[0072] The evolutionary game matrix is ​​shown in the table below:

[0073] Table 2. Critical Game Matrix of Energy Storage Cost Dispersion

[0074]

[0075] The evolutionary game matrix is ​​established as follows:

[0076]

[0077] Among them, Z a Z b Z c Each represents a different strategy combination. n ×b n ×c n The benefits to the power supply side, the grid side, and the load side under (n=1∪n=2).

[0078] Specifically, under the combination of power source side purchasing energy storage capacity, grid side purchasing energy storage capacity, and user side demand response strategy, the benefits for the power source side, grid side, and load side are as follows:

[0079]

[0080] Under the combined strategy of purchasing energy storage capacity on the power generation side, purchasing energy storage capacity on the grid side, and no demand response on the user side, the benefits to the power generation side, grid side, and load side are as follows:

[0081] (Z a ) a1，b1，c2 =Q a1 (P a1 -C a )+α1(Q a -Q a1 (P) a1 -C b1 )+(1-α1)(Q a -Qa1 (P) a1 -C a )

[0082] (Z b ) a1，b1，c2 =Q a1 (P b -P a1 )+α1(Q a -Q a1 (P) b -P a1 )+(1-α1)(Q a -Q a1 (P) b -C b2 )

[0083] (Z c ) a1，b1，c2 =BQ a P b

[0084] Under the combined strategy of the power generation side purchasing energy storage capacity, the grid side not purchasing energy storage capacity, and the user side demand response strategy, the benefits to the power generation side, the grid side, and the load side are as follows:

[0085] (Z a ) a1，b2，c1 =(Q a1 (P a1 -C a )+α1(Q a -Q a1 (P) a1 -C b1 )+(1-α1)(Q a -Q a1 (P) a1 -C a )

[0086] (Z b ) a1，b2，c1 =Q a1 (P b -P a1 )+α1(Q a -Q a1 (P) b -P a1 )+(1-α1)(Q a -Q a1 (P) a1 -C b3 )

[0087] (Z c ) a1，b2，c1 =BQ a P b+(1-α1)(Q a -Q a1 C b3 )

[0088] Under the strategy combination of the power generation side purchasing energy storage capacity, the grid side not purchasing energy storage capacity, and the user side not demand response, the benefits to the power generation side, the grid side, and the load side are as follows:

[0089] (Z a ) a1，b2，c2 =Q a1 (P a1 -C a )+(Q a -Q a1 (P) a1 -C b1 )

[0090] (Z b ) a1，b2，c2 =Q a1 (P b -P a1 )+(Q a -Q a1 (P) b -P a1 )

[0091] (Z c ) a1，b2，c2 =BQ a P b

[0092] Under a combination of strategies involving no energy storage purchases by the power generation side, energy storage purchases by the grid side, and demand response by the user side, the benefits for the power generation side, grid side, and load side are as follows:

[0093] (Z a ) a2，b1，c1 =(Q a (P a1 -C a )-β

[0094] (Z b ) a2，b1，c1 =Q a (P b -P a1 )-α2(Q a -Q a1 C b2 -(1-α2)(Q a -Q a1 C b3 +β

[0095] (Z c ) a2，b1，c1 =BQ aP b +(1-α2)(Q a -Q a1 C b3 )

[0096] Under the combined strategy of no energy storage capacity purchase by the power generation side, energy storage capacity purchase by the grid side, and no demand response by the user side, the benefits to the power generation side, grid side, and load side are as follows:

[0097] (Z a Z b Z c ) a2，b1，c2 =(Q a (P a1 -C a )-β,Q a (P b -P a1 )-(Q a -Q a1 C b2 +β,BQ a P b )

[0098] Under a combination of power generation and grid-side energy storage capacity not being purchased, and user-side demand response strategies, the benefits to the power generation, grid, and load sides are as follows:

[0099] (Z a Z b Z c ) a2，b2，c1 =(Q a (P a1 -C a )-β,Q a (P b -P a1 )-(Q a -Q a1 C b3 +β,BQ a P b +(Q a -Q a1 C b3 )

[0100] Under a strategy combination where the power supply side does not purchase energy storage capacity, the grid side does not purchase energy storage capacity, and the user side does not require demand response, the benefits to the power supply side, the grid side, and the load side are as follows:

[0101] (Z a Z b Z c ) a2，b2，c2 =(Q a1 (P a1 -C a)-β,Q a1 (P b -P a1 )+β,B-B1-Q a1 P b )

[0102] Among them, P a1 The grid connection price per unit of electricity generated on the power supply side; P b Electricity price per unit of electricity purchased by the user; Q a Q represents the total power generation planned for trading on the power supply side. a1 α1 represents the maximum available power generation on the power source side without purchasing energy storage capacity; α2 represents the proportion of power output compensated by power source-side energy storage when supply and demand are unbalanced; C represents the proportion of power output compensated by grid-side energy storage or inter-regional power transmission when supply and demand are unbalanced. a The levelized cost of electricity (LCOE) for power supply without the application of flexible resources; C b1 The levelized cost of electricity (LCOE) for power-side application of flexible resources; C b2 The levelized cost of electricity (LCOE) for grid-side application of flexible resources; C b3 β is the cost of demand response for load-side applications; B is the penalty paid for failure to supply power as contracted due to the power supply side not using flexible resources; B is the benefit gained from normal production on the load side; B1 is the benefit lost due to abnormal production on the load side.

[0103] (2) Based on the evolutionary game matrix, calculate the expected payoff of the power supply side subject's strategy selection and its replication dynamic equation.

[0104] Specifically, the expected return U of the power supply entity choosing to purchase energy storage capacity versus not purchasing energy storage capacity. a1 U a2 They are respectively:

[0105] Ua1=y[z(Za) a1，b1，c1 +(1-z)(Za) a1，b1，c2 ]+(1-y)[z(Za) a1，b2，c1 +(1-z)(Za) a1，b2，c2 ]

[0106] Ua2=y[z(Za) a2，b1，c1 +(1-z)(Za) a2，b1，c2 ]+(1-y)[z(Za) a2，b2，c1 +(1-z)(Za) a2，b2，c2 ]

[0107] The dynamic equation for the strategy of whether the power supply entity purchases energy storage capacity is:

[0108]

[0109] (3) Based on the evolutionary game matrix, calculate the expected returns of the main strategy selection of the power grid side and its replication dynamic equation.

[0110] Specifically, the expected return U of the grid-side entity choosing to purchase energy storage capacity versus not purchasing energy storage capacity. b1 U b2 They are respectively:

[0111] U b1 =x[z(Z) b ) a1，b1，c1 +(1-z)(Z b ) a1，b1，c2 ]+(1-x)[z(Z b ) a2，b1，c1 +(1-z)(Z b ) a2，b1，c2 ]

[0112] U b2 =x[z(Z) b ) a1，b2，c1 +(1-z)(Z b ) a1，b2，c2 ]+(1-x)[z(Z b ) a2，b2，c1 +(1-z)(Z b ) a2，b2，c2 ]

[0113] The dynamic equation for the strategy of whether the grid-side entity should purchase energy storage capacity is:

[0114]

[0115] (4) Based on the evolutionary game matrix, calculate the expected payoff of the user-side agent's strategy choice and its replication dynamic equation. Specifically, calculate the expected payoff U of the user-side agent choosing to respond to the demand and rejecting the demand. c1 U c2 They are respectively:

[0116] U c1 =x[y(Z) c ) a1，b1，c1 +(1-y)(Z c ) a1，b2，c1 ]+(1-x)[y(Z c ) a2，b1，c1 +(1-y)(Z c ) a2，b2，c1 ]

[0117] U c2 =x[y(Z) c ) a1，b1，c2 +(1-y)(Z c ) a1，b2，c2]+(1-x)[y(Z c ) a2，b1，c2 +(1-y)(Z c ) a2，b2，c2 ]

[0118] The strategy for whether the user-side entity uses energy storage technology is replicated using the dynamic equation:

[0119]

[0120] (5) Conduct evolutionary game analysis and analyze the evolutionary game scenario.

[0121] (6) Considering the changes in user willingness to respond to the policy that may be adopted in response to the outcome of each evolutionary game, a Markov chain is used to simulate the changes in user willingness probability, and then return to step (1) to continue the evolutionary game.

[0122] Specifically, considering the changes in users' willingness to respond to demands in light of the possible policies that may be adopted based on the outcome of each evolutionary game, the probability of users favoring responding or not responding is obtained after implementing the corresponding policies; a state space {1,2} is established, where state 1 represents responding to demands and state 2 represents not responding; the unchanged demand response during the survey is denoted as p. 11 The transformation from a demand response to a rejection is denoted as p. 12 Correspondingly, the rejection of demand response and the transformation into demand response is denoted as p. 21 If the original attitude is not changed, it is recorded as p. 22 Based on this, a one-step transition probability matrix is ​​constructed.

[0123]

[0124] Considering that the user demand response only takes into account the current state, it can be understood as a process without aftereffects, and is regarded as an irreducible, aperiodic Markov process. This discrete Markov chain is considered to be an ergodic state. Based on this, the probability of the user demand response is updated using the following formula:

[0125]

[0126] The Markov chain is used to simulate the change in user willingness probability, and then the game is continued by returning to step (1).

[0127] The evolutionary game theory method for energy storage cost mitigation provided by this invention differs from traditional cost mitigation methods in that it determines the probability of adopting energy storage technology by analyzing the behavior of three market participants, thereby constructing an evolutionary game matrix. Based on this matrix, the expected returns of different participants and the replication dynamic process are determined. Furthermore, a Markov chain is applied to represent the impact of measures taken in response to each evolutionary game outcome on user-side demand response behavior, which is then fed back into the matrix for the next evolutionary game. This allows for a more accurate description of the cost mitigation results.

[0128] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0129] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0130] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0131] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0132] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A cost-distribution rational game theory method for energy storage, characterized in that, Includes the following steps: (1) Collect relevant information on the main entities on the power supply side, grid side, and user side in the target area, and establish an evolutionary game matrix for energy storage cost diversion; (2) Based on the evolutionary game matrix, calculate the expected payoff of the agent's strategy selection on the power supply side and its replication dynamic equation; (3) Based on the evolutionary game matrix, calculate the expected payoff of the main strategy selection of the power grid side and its replication dynamic equation; (4) Based on the evolutionary game matrix, calculate the expected payoff of the user-side subject's strategy selection and its replication dynamic equation; (5) Conduct evolutionary game theory and analyze the game theory scenarios; (6) Considering the changes in user willingness to respond to the policy that may be adopted in response to the outcome of each evolutionary game, a Markov chain is used to simulate the changes in user willingness probability, and then return to step (1) to continue the evolutionary game; In step (1), the evolutionary game matrix is ​​established as follows: Among them, Z a Z b Z c Each represents a different strategy combination. n ×b n ×c n The benefits to the power supply side, grid side, and load side under (n=1∪n=2) conditions; Under a combination of strategies involving the power generation side purchasing energy storage capacity, the grid side purchasing energy storage capacity, and the user side demand response, the benefits for the power generation side, the grid side, and the load side are as follows: Under the combined strategy of purchasing energy storage capacity on the power generation side, purchasing energy storage capacity on the grid side, and no demand response on the user side, the benefits to the power generation side, grid side, and load side are as follows: Under the combined strategy of the power generation side purchasing energy storage capacity, the grid side not purchasing energy storage capacity, and the user side demand response strategy, the benefits to the power generation side, the grid side, and the load side are as follows: Under the strategy combination of the power generation side purchasing energy storage capacity, the grid side not purchasing energy storage capacity, and the user side not demand response, the benefits to the power generation side, the grid side, and the load side are as follows: Under a combination of strategies involving no energy storage purchases by the power generation side, energy storage purchases by the grid side, and demand response by the user side, the benefits for the power generation side, grid side, and load side are as follows: Under the combined strategy of no energy storage capacity purchase by the power generation side, energy storage capacity purchase by the grid side, and no demand response by the user side, the benefits to the power generation side, grid side, and load side are as follows: Under a combination of power generation and grid-side energy storage capacity not being purchased, and user-side demand response strategies, the benefits to the power generation, grid, and load sides are as follows: Under a strategy combination where the power supply side does not purchase energy storage capacity, the grid side does not purchase energy storage capacity, and the user side does not require demand response, the benefits to the power supply side, the grid side, and the load side are as follows: Among them, P a1 The grid connection price per unit of electricity generated on the power supply side; P b Electricity price per unit of electricity purchased by the user; Q a Q represents the total power generation planned for trading on the power supply side. a1 α1 represents the maximum available power generation on the power source side without purchasing energy storage capacity; α2 represents the proportion of power output compensated by power source-side energy storage when supply and demand are unbalanced; C represents the proportion of power output compensated by grid-side energy storage or inter-regional power transmission when supply and demand are unbalanced. a The levelized cost of electricity (LCOE) for power supply without the application of flexible resources; C b1 The levelized cost of electricity (LCOE) for power-side application of flexible resources; C b2 The levelized cost of electricity (LCOE) for grid-side application of flexible resources; C b3 β is the cost of demand response for load-side applications; B is the penalty paid for failure to supply power as contracted due to the power supply side not using flexible resources; B is the benefit gained from normal production on the load side; B1 is the benefit lost due to abnormal production on the load side. In step (6), considering the changes in user demand response intentions based on the possible policies to be adopted for each evolutionary game outcome, after implementing the corresponding policies, the probability of users favoring demand response or not favoring demand response is obtained; a state space {1,2} is established, where state 1 represents demand response and state 2 represents not favoring demand response; during the survey, the demand response remains unchanged and is denoted as... The shift from a demand response to a rejection is denoted as Accordingly, the rejection of demand response and the shift to demand response is denoted as... Record without changing the original attitude Based on this, a one-step transition probability matrix is ​​constructed. Considering that user demand response only takes into account the current state, it can be understood as a process without aftereffects, and is regarded as an irreducible, aperiodic Markov process. The discrete Markov chain is considered to be ergodic to states. Based on this, the probability of user demand response is updated using the following formula: The Markov chain is used to simulate the change in user willingness probability, and then the process returns to step (1) to continue the evolution of the game.

2. The energy storage cost decentralization chemical game method according to claim 1, characterized in that, In step (2), the expected return U of the power supply entity choosing to purchase energy storage capacity versus not purchasing energy storage capacity is... a1 U a2 They are respectively: The dynamic equation for the strategy of whether the power supply entity purchases energy storage capacity is: 。 3. The energy storage cost decentralization chemical game method according to claim 1, characterized in that, In step (3), the expected return U of the grid-side entity choosing to purchase energy storage capacity versus not purchasing energy storage capacity is... b1 U b2 They are respectively: The dynamic equation for the strategy of whether the grid-side entity should purchase energy storage capacity is: 。 4. The energy storage cost decentralization evolutionary game method according to claim 1, characterized in that, In step (4), the expected benefit U of the user-side subject choosing to respond to the demand and reject the demand response is determined. c1 U c2 They are respectively: The strategy for whether the user-side entity uses energy storage technology is replicated using the dynamic equation: 。

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