New energy market dynamic evolution method and system based on game decision

Abstract

The invention discloses a game decision-based new energy market dynamic evolution method and system, and relates to the technical field of new energy, and the method comprises the steps: building a three-party evolution game model of a new energy market based on the interaction relation and benefit relation of producers, consumers and supervisors; based on a three-party evolutionary game model, establishing a three-dimensional replication dynamic equation set for expected benefits of three parties; an equilibrium point is obtained according to the three-dimensional replication dynamic equation set, stability analysis is carried out, and an evolution stability strategy is obtained; and drawing a dynamic evolution process of the new energy market according to the three-party evolutionary game model by applying a system dynamics method. According to the method, the finite rationality of multiple subjects is considered, a new energy market three-party evolutionary game model considering multiple factors is designed, a set of evolutionary stability analysis method for the green product market is formulated, and the stable evolutionary result provides theoretical support for supervisors to formulate related policies and develop the green product market.

Description

Technical Field

[0001] The present invention relates to the field of new energy technology, and more specifically to a new energy market dynamic evolution method and system based on game decision-making. Background Art

[0002] For producers, as product suppliers in the green market, the green transformation of enterprises has received widespread attention. Existing research mainly focuses on market incentives, government policy promotion, and competition among enterprises in the same industry. The benefits brought by green transformation to enterprises are the main motivation for enterprise transformation, and the adoption of new green technologies will also improve the reputation of enterprises through media attention. In addition, in the face of the continuous upgrading of environmental regulations, enterprises face greater policy risks. Enterprises taking the lead in developing or adopting green technologies can reduce policy risks and avoid greater losses caused by being forced to adopt green technologies;

[0003] For consumers, green consumption has attracted the attention of many scholars due to its positive impact on environmental protection. From the perspective of research, it includes the causal effect of energy consumption and economic development, energy consumption and carbon emissions, energy utilization efficiency, and energy consumption structure.

[0004] For supervisors, as the main promoters of the green product market, existing technologies mostly study the relationship between supervisors and producers and consumers in the market. From the perspective of supervisors and producers, government subsidies have a positive effect on green supply chain management. Furthermore, based on the background of duopoly, the supply chain model under the government subsidy mechanism is studied to analyze the positive role of the government in green supply chain management.

[0005] Some scholars also focus on the impact of the interaction between various participants in the low-carbon green market on the market. From the perspective of emission reduction research and development, the reverse solution method is used to study how the government's carbon tax policy and the cooperative research and development decisions of suppliers and manufacturers jointly affect the optimal emission reduction of the supply chain.

[0006] However, existing literature mostly focuses on studying the mutual influence and joint action between supervisors and producers, and supervisors and consumers, and rarely considers the dynamic interaction among the three parties at the same time.

[0007] Therefore, how to provide a method and system for the dynamic evolution of the new energy market based on game decision-making, consider the interaction of multiple parties and limited rationality to construct a game decision-making model, combine actual data, describe the dynamic process of decision-making evolution, better verify the model and conduct quantitative analysis of the market is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0008] In view of this, the present invention provides a new energy market dynamic evolution method and system based on game decision-making, takes into account the limited rationality of multiple parties, designs a three-party evolutionary game model of the new energy market taking into account multiple factors, and formulates a set of evolutionary stability analysis methods for the green product market. The stable evolution results provide theoretical support for supervisors to formulate relevant policies and develop the green product market.

[0009] In order to achieve the above purpose, the present invention adopts the following technical solution: a new energy market dynamic evolution method based on game decision-making, comprising:

[0010] Based on the interactive relationship and interest relationship among producers, consumers and supervisors, a three-party evolutionary game model of the new energy market is established;

[0011] Based on the three-party evolutionary game model, a three-dimensional replication dynamic equation set is established for the expected benefits of the three parties;

[0012] The equilibrium point is obtained based on the three-dimensional replication dynamic equations, and stability analysis is performed to obtain the evolutionary stability strategy;

[0013] Using the system dynamics method, the dynamic evolution process of the new energy market is drawn based on the three-party evolutionary game model.

[0014] Preferably, the method further includes: analyzing the impact of decision variables and environmental variables on the new energy market in combination with the convergence path of dynamic evolution and the evolutionary stabilization strategy.

[0015] Preferably, a three-dimensional replication dynamic equation system is established for the expected benefits of the three parties:

[0016] The replication dynamics equation of the supervisor decision is expressed as:

[0017]

[0018] Among them, U x1 represents the expected benefit of the supervisor when choosing a supervision strategy, U x2 represents the expected benefit of the supervisor when choosing the non-supervision strategy, represents the average benefit of the supervisor, x represents the selection ratio of the supervision strategy, 1-x represents the selection ratio of the non-supervision strategy, y represents the selection ratio of the production strategy, z represents the selection ratio of the consumption strategy, α represents the subsidy coefficient of the supervisor to the producer, β represents the subsidy coefficient of the supervisor to the consumer, S represents the supervision cost, F represents the fine on the producer, and L represents the loss when the supervisor does not supervise; P1 represents the additional cost that consumers need to pay when consuming green products when producers provide new energy products; P2 represents the additional information and conversion costs and time costs that consumers need to pay when consuming green products when producers do not provide new energy products;

[0019] The replication dynamics equation for producer decision is expressed as:

[0020]

[0021] in, represents the average revenue of producers, C1 is the additional cost of producing new energy products; R1 is the additional revenue obtained by producers when supervisors and consumers choose supervision strategy and consumption strategy respectively; R2 is the additional revenue obtained by producers when supervisors and consumers choose no supervision strategy and no consumption strategy respectively;

[0022] The replication dynamic equation of consumer decision making is expressed as:

[0023]

[0024] in, It represents the average revenue of producers.

[0025] Preferably, according to the expected benefits of the supervisor when choosing the supervision strategy and the expected benefits of the non-supervision strategy, the average benefit of the supervisor is obtained as:

[0026]

[0027] Among them, U x1 represents the expected benefit of the supervisor when choosing a supervision strategy, U x2 represents the expected return of the supervisor when choosing the unsupervised strategy, x represents the selection ratio of the supervised strategy, and 1-x represents the selection ratio of the unsupervised strategy;

[0028] According to the expected profit of producers when choosing production strategy and the expected profit when not choosing production strategy, the average profit of producers is:

[0029]

[0030] Among them, U y1 represents the expected profit of the producer when choosing a production strategy, U y2 represents the expected profit of the producer when choosing the non-production strategy, y represents the selection ratio of the production strategy, and 1-y represents the selection ratio of the non-production strategy;

[0031] According to the expected benefits of consumers when choosing consumption strategies and the expected benefits when not choosing consumption strategies, the average benefits of consumers are:

[0032]

[0033] Among them, U z1 represents the expected benefit of consumers when choosing consumption strategies, U z2represents the expected benefit of the consumer when choosing the non-consumption strategy, z represents the selection ratio of the consumption strategy, and 1-z represents the selection ratio of the non-consumption strategy.

[0034] Preferably, let F(x) = 0, F(y) = 0, F(z) = 0, and we can get 9 equilibrium points that make the supervisor, producer and consumer all reach a stable state: A1(0,0,0), A2(1,0,0), A3(0,1,0), A4(0,0,1), A5(1,1,0), A6(1,0,1), A7(0,1,1), A8(1,1,1), A9(x * ,y * ,z * );

[0035] Among them, A9(x * ,y * ,z * ) is the internal equilibrium point, which is in a non-asymptotically stable state, and A1~A8 are local equilibrium points, which are in an asymptotically stable state;

[0036] The Jacobian matrix is ​​used to analyze the stability of each local equilibrium point.

[0037] Preferably, when the eigenvalues ​​of the Jacobian matrix corresponding to the local equilibrium point are all negative, the local equilibrium point is asymptotically stable, and the strategy group represented by the local equilibrium point is called an evolutionary stable strategy;

[0038] When the eigenvalues ​​of the Jacobian matrix corresponding to the local equilibrium point are all positive, the local equilibrium point is an unstable point;

[0039] When one or two eigenvalues ​​of the Jacobian matrix corresponding to a local equilibrium point are greater than 0, the local equilibrium point is a saddle point.

[0040] Preferably, when When , no matter what value x takes, F(x) = 0, and the supervisor's decision remains stable; when When F′(x)| x＝0 <0, F′(x)| x＝1 >0, then x=0 is the equilibrium point; when When F′(x)| x＝0 >0,F′(x)| x＝1 <0, at this time x=1 is the equilibrium point;

[0041] when When , no matter what value y takes, F(y) = 0, and the producer's decision remains stable; when When F′(y)| y＝0 <0, F′(y)| y＝1 >0, then y=0 is the equilibrium point; when When F′(y)| y＝0 >0,F′(y)| y＝1 <0, at this time y = 1 is the equilibrium point;

[0042] when When , no matter what value z takes, F(z) = 0, and the consumer's decision remains stable; when When F′(z)| z＝0 <0,F′(z)| z＝1 >0, then z=0 is the equilibrium point; when When F′(z)| z＝0 >0,F′(z)| z＝1 <0, at this time z=1 is the equilibrium point.

[0043] Preferably, the Jacobian matrix is ​​expressed as:

[0044]

[0045] in,

[0046] a 11 =(1-2x)[yzβP2-y(αC1+F+L)-zβ(P1+P2)+F+LS];

[0047] a 12 =x(1-x)(zβP2-αC1-FL);

[0048] a 13 =x(1-x)(yβP2-βP1-βP2);

[0049] a 21 =y(1-y)[z(R1-R2)+αC1+F];

[0050] a 22 =(1-2y)[xz(R1-R2)+x(αC1+F)+zR2-C1];

[0051] a 23 =y(1-y)[x(R1-R2)+R2];

[0052] a 31 =z(1-z)(-yβP2+βP1+βP2);

[0053] a 32 =z(1-z)(-xβP2+P2);

[0054] a 33 =(1-2z)[xβ(P1+P2)-xyβP2+yP2+U1-P1-P2].

[0055] Preferably, a new energy market dynamic evolution system based on game decision-making includes:

[0056] Model building module, which is used to establish a three-party evolutionary game model of the new energy market based on the interactive relationship and interest relationship among producers, consumers and supervisors;

[0057] An equation group establishment module, used for establishing a three-dimensional replication dynamic equation group for the expected benefits of the three parties based on the three-party evolutionary game model;

[0058] The stability analysis module is used to obtain the equilibrium point based on the three-dimensional replication dynamic equations, and to perform stability analysis to obtain the evolutionary stability strategy;

[0059] The dynamic evolution module is used to draw the dynamic evolution process of the new energy market according to the three-party evolutionary game model by using the system dynamics method.

[0060] Through the above technical solutions, it can be known that compared with the prior art, the present invention discloses a method and system for the dynamic evolution of a new energy market based on game decision-making, including: establishing a three-party evolutionary game model of the new energy market based on the interactive relationship and interest relationship among producers, consumers and supervisors; establishing a three-dimensional replication dynamic equation group for the expected benefits of the three parties based on the three-party evolutionary game model; obtaining the equilibrium point according to the three-dimensional replication dynamic equation group, and performing stability analysis to obtain an evolutionary stability strategy; using the system dynamics method, the dynamic evolution process of the new energy market is drawn according to the three-party evolutionary game model. The present invention considers the interaction and limited rationality between multiple subjects to construct an evolutionary game model; the constructed model contains the government's actual important policy variables, so that the model can better match reality; combined with actual data, the system dynamics method is used to depict the dynamic process of decision-making evolution, better verify the model and conduct quantitative analysis of the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0062] Figure 1 A schematic diagram of decision evolution using a system dynamics method is provided for an embodiment of the present invention.

[0063] FIG2( a ) is a schematic diagram showing the influence of the initial values ​​of y and z on the evolution of x provided by an embodiment of the present invention, wherein the initial values ​​of y and z randomly selected have an influence on x.

[0064] FIG2( b ) is a schematic diagram showing the influence of the initial value of z randomly selected on the evolution of x when y=0, in the influence of the initial value of y and z on the evolution of x provided by an embodiment of the present invention.

[0065] FIG2( c ) is a schematic diagram showing the influence of the initial value of y randomly selected on the evolution of x when z=0, in the influence of the initial value of y and z on the evolution of x provided by an embodiment of the present invention.

[0066] FIG3( a ) is a schematic diagram showing the influence of the initial values ​​of x and z on the evolution of y provided by an embodiment of the present invention, wherein the initial values ​​of x and z randomly selected have an influence on y.

[0067] FIG3( b ) is a schematic diagram showing the influence of the initial value of z randomly selected on y when x=0, in the influence of the initial values ​​of x and z on the evolution of y provided by an embodiment of the present invention.

[0068] FIG3( c ) is a schematic diagram showing the influence of the initial value of x and z on the evolution of y provided by an embodiment of the present invention, when z=0, and the influence of the initial value of x randomly selected on y.

[0069] FIG4( a ) is a schematic diagram showing the influence of randomly selected initial values ​​of x and y on z in the influence of initial values ​​of x and y on the evolution of z provided by an embodiment of the present invention.

[0070] FIG4( b ) is a schematic diagram showing the influence of the initial value of x and y on the evolution of z provided by an embodiment of the present invention, when x=0, and the influence of the initial value of y randomly selected on z.

[0071] FIG4( c ) is a schematic diagram showing the influence of the initial value of x and y on the evolution of z provided by an embodiment of the present invention, when y=0, and the influence of the initial value of x randomly selected on z.

[0072] FIG5(a) is an evolution path of A1(0,0,0) provided in an embodiment of the present invention.

[0073] FIG5( b ) is an evolution path of A2(1,0,0) provided in an embodiment of the present invention.

[0074] FIG5(c) is an evolution path of A3(0,1,0) provided in an embodiment of the present invention.

[0075] FIG5(d) is an evolution path of A4(0,0,1) provided in an embodiment of the present invention.

[0076] FIG5(e) is an evolution path of A5(1,1,0) provided in an embodiment of the present invention.

[0077] FIG5(f) is an evolution path of A6(1,0,1) provided in an embodiment of the present invention.

[0078] FIG5(g) is an evolution path of A8(1,1,1) provided in an embodiment of the present invention.

[0079] FIG6( a ) shows the effect of the change of the initial value of P1 on the evolution of x according to an embodiment of the present invention.

[0080] FIG6( b ) shows the influence of the change of the initial value of P1 on the evolution of y provided by an embodiment of the present invention.

[0081] FIG6( c ) shows the effect of the change of the initial value of P1 on the evolution of z provided by an embodiment of the present invention.

[0082] FIG. 7( a ) shows the effect of the change of the initial value of U1 on the evolution of x provided by an embodiment of the present invention.

[0083] FIG. 7( b ) shows the effect of the change of the initial value of U1 on the evolution of y provided in an embodiment of the present invention.

[0084] FIG. 7( c ) shows the effect of the change of the initial value of U1 on the evolution of z provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0085] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0086] The embodiment of the present invention discloses a method and system for the dynamic evolution of a new energy market based on game decision-making. Taking into account the limited rationality of multiple parties, a three-party evolutionary game model of the new energy market taking multiple factors into consideration is designed, and a set of evolutionary stability analysis methods for the green product market is formulated. The stable evolution results provide theoretical support for supervisors to formulate relevant policies and develop the green product market.

[0087] The embodiment of the present invention discloses a new energy market dynamic evolution method based on game decision-making, comprising:

[0088] Based on the interactive relationship and interest relationship among producers, consumers and supervisors, a three-party evolutionary game model of the new energy market is established;

[0089] Based on the three-party evolutionary game model, a three-dimensional replication dynamic equation set is established for the expected benefits of the three parties;

[0090] The equilibrium point is obtained based on the three-dimensional replication dynamic equations, and stability analysis is performed to obtain the evolutionary stability strategy;

[0091] Based on the evolutionary stable strategy, the influence of the value range and relationship of the three-party decision variables on the game results is analyzed;

[0092] Using the system dynamics method, the dynamic evolution process of the new energy market is drawn based on the three-party evolutionary game model.

[0093] Specifically, it also includes: combining the convergence path of dynamic evolution and the evolutionary stabilization strategy to analyze the impact of decision variables and environmental variables on the new energy market.

[0094] Specifically, a three-dimensional replication dynamic equation group is established for the expected benefits of the three parties:

[0095] The replication dynamics equation of the supervisor decision is expressed as:

[0096]

[0097] Among them, U x1 represents the expected benefit of the supervisor when choosing a supervision strategy, U x2 represents the expected benefit of the supervisor when choosing the non-supervision strategy, represents the average benefit of the supervisor, x represents the selection ratio of the supervision strategy, 1-x represents the selection ratio of the non-supervision strategy, y represents the selection ratio of the production strategy, z represents the selection ratio of the consumption strategy, α represents the subsidy coefficient of the supervisor to the producer, β represents the subsidy coefficient of the supervisor to the consumer, S represents the supervision cost, F represents the fine on the producer, and L represents the loss when the supervisor does not supervise; P1 represents the additional cost that consumers need to pay when consuming green products when producers provide new energy products; P2 represents the additional information and conversion costs and time costs that consumers need to pay when consuming green products when producers do not provide new energy products;

[0098] The replication dynamics equation for producer decision is expressed as:

[0099]

[0100] in, represents the average revenue of producers, C1 is the additional cost of producing new energy products; R1 is the additional revenue obtained by producers when supervisors and consumers choose supervision strategy and consumption strategy respectively; R2 is the additional revenue obtained by producers when supervisors and consumers choose no supervision strategy and no consumption strategy respectively;

[0101] The replication dynamic equation of consumer decision making is expressed as:

[0102]

[0103] in, It represents the average revenue of producers.

[0104] Specifically, according to the expected benefits of the supervisor when choosing the supervision strategy and the expected benefits of the non-supervision strategy, the average benefit of the supervisor is:

[0105]

[0106] Among them, U x1 represents the expected benefit of the supervisor when choosing a supervision strategy, U x2 represents the expected return of the supervisor when choosing the unsupervised strategy, x represents the selection ratio of the supervised strategy, and 1-x represents the selection ratio of the unsupervised strategy;

[0107] According to the expected profit of producers when choosing production strategy and the expected profit when not choosing production strategy, the average profit of producers is:

[0108]

[0109] Among them, U y1 represents the expected profit of the producer when choosing a production strategy, U y2 represents the expected profit of the producer when choosing the non-production strategy, y represents the selection ratio of the production strategy, and 1-y represents the selection ratio of the non-production strategy;

[0110] According to the expected benefits of consumers when choosing consumption strategies and the expected benefits when not choosing consumption strategies, the average benefits of consumers are:

[0111]

[0112] Among them, U z1 represents the expected benefit of consumers when choosing consumption strategies, U z2 represents the expected benefit of the consumer when choosing the non-consumption strategy, z represents the selection ratio of the consumption strategy, and 1-z represents the selection ratio of the non-consumption strategy.

[0113] Specifically, let F(x) = 0, F(y) = 0, F(z) = 0, and we can get 9 equilibrium points that make the supervisor, producer, and consumer all reach a stable state: A1(0,0,0), A2(1,0,0), A3(0,1,0), A4(0,0,1), A5(1,1,0), A6(1,0,1), A7(0,1,1), A8(1,1,1), A9(x * ,y * ,z * );

[0114] Among them, A9(x * ,y * ,z * ) is the internal equilibrium point, which is in a non-asymptotically stable state, and A1~A8 are local equilibrium points, which are in an asymptotically stable state;

[0115] The Jacobian matrix is ​​used to analyze the stability of each local equilibrium point.

[0116] Specifically, when the eigenvalues ​​of the Jacobian matrix corresponding to the local equilibrium point are all negative, the local equilibrium point is asymptotically stable, and the strategy group represented by the local equilibrium point is called an evolutionary stable strategy;

[0117] When the eigenvalues ​​of the Jacobian matrix corresponding to the local equilibrium point are all positive, the local equilibrium point is an unstable point;

[0118] When one or two eigenvalues ​​of the Jacobian matrix corresponding to a local equilibrium point are greater than 0, the local equilibrium point is a saddle point.

[0119] Specifically, when When , no matter what value x takes, F(x) = 0, and the supervisor's decision remains stable; when When F′(x)| x＝0 <0, F′(x)| x＝1 >0, then x=0 is the equilibrium point; when When F′(x)| x＝0 >0,F′(x)| x＝1 <0, at this time x=1 is the equilibrium point;

[0120] when When , no matter what value y takes, F(y) = 0, and the producer's decision remains stable; when When F′(y)| y＝0 <0, F′(y)| y＝1 >0, then y=0 is the equilibrium point; when When F′(y)| y＝0 >0,F′(y)| y＝1 <0, at this time y = 1 is the equilibrium point;

[0121] when When , no matter what value z takes, F(z) = 0, and the consumer's decision remains stable; when When F′(z)| z＝0 <0,F′(z)| z＝1 >0, then z=0 is the equilibrium point; when When F′(z)| z＝0 >0,F′(z)| z＝1 <0, at this time z=1 is the equilibrium point.

[0122] Specifically, the Jacobian matrix is ​​expressed as:

[0123]

[0124] in,

[0125] a 11 =(1-2x)[yzβP2-y(αC1+F+L)-zβ(P1+P2)+F+LS];

[0126] a 12 =x(1-x)(zβP2-αC1-FL);

[0127] a 13 =x(1-x)(yβP2-βP1-βP2);

[0128] a 21 =y(1-y)[z(R1-R2)+αC1+F];

[0129] a 22 =(1-2y)[xz(R1-R2)+x(αC1+F)+zR2-C1];

[0130] a 23 =y(1-y)[x(R1-R2)+R2];

[0131] a 31 =z(1-z)(-yβP2+βP1+βP2);

[0132] a 32 =z(1-z)(-xβP2+P2);

[0133] a 33 =(1-2z)[xβ(P1+P2)-xyβP2+yP2+U1-P1-P2].

[0134] The embodiment of the present invention also discloses a new energy market dynamic evolution system based on game decision-making, including:

[0135] Model building module, which is used to establish a three-party evolutionary game model of the new energy market based on the interactive relationship and interest relationship among producers, consumers and supervisors;

[0136] An equation group establishment module, used for establishing a three-dimensional replication dynamic equation group for the expected benefits of the three parties based on the three-party evolutionary game model;

[0137] The stability analysis module is used to obtain the equilibrium point based on the three-dimensional replication dynamic equations, and to perform stability analysis to obtain the evolutionary stability strategy;

[0138] The dynamic evolution module is used to draw the dynamic evolution process of the new energy market according to the three-party evolutionary game model by using the system dynamics method.

[0139] In a specific embodiment of the present invention, the above-mentioned method for dynamic evolution of new energy market based on game decision-making is applied to the new energy vehicle market, and the three parties involved are the government (supervisor), passenger vehicle manufacturers (producers) and consumers. Figure 1 shown.

[0140] Specifically, the embodiment of the present invention first introduces government policy parameters (such as double-point policy, etc.) based on the interactive relationship and interest relationship among the government, passenger car manufacturers and consumers, and establishes a three-party evolutionary game model of the new energy vehicle market;

[0141] Secondly, based on the three-party evolutionary game model, a three-dimensional replication dynamic equation set is established for the expected returns of different game players;

[0142] Thirdly, the equilibrium point is obtained based on the three-dimensional replication dynamic equations, and the evolutionary stable strategy ESS is obtained through stability analysis, which explores the impact of the value range and relationship of the important decision variables of the three parties on the game results;

[0143] Finally, the system dynamics method is used to draw the dynamic evolution process based on the established evolutionary game model, and the impact of important policy variables and environmental variables on the market is analyzed in combination with the dynamic evolution convergence path and the evolutionary stability strategy ESS.

[0144] The embodiment of the present invention takes into account the limited rationality of multiple parties, designs a three-party evolutionary game model of the new energy vehicle market that takes into account multiple factors such as the double-credit policy, corporate reputation, and the level of green and low-carbon society, and develops a set of evolutionary stability analysis methods for the green product market. Its stable evolution results provide theoretical support for the government to formulate relevant policies and develop the green product market.

[0145] Specifically, 1. Model assumptions and parameters:

[0146] The embodiment of the present invention assumes that the government, enterprises, and consumers can only make limited rational decisions under incomplete information. The three parties continuously adjust their decisions by analyzing the decision-making environment and the strategies of other entities. After a period of time, the system may reach a certain stable state.

[0147] For the proposition of building a low-carbon supply chain, the decisions of the three parties, government, enterprises and consumers, are crucial. For the government, there are two strategies to choose from: "regulation" and "no regulation", with selection ratios of x and 1-x respectively. Among them, when the government chooses the strategy of "regulation", it needs to invest costs including regulatory manpower, management costs and policy support. For enterprises, there are two strategies to choose from: "production of new energy vehicles" and "no production of new energy vehicles", with selection ratios of y and 1-y respectively. Among them, when passenger car companies choose the strategy of "production of new energy vehicles", they need to make low-carbon efforts in product research and development, production and manufacturing, publicity, etc., and need to invest additional costs including new technologies and funds, but can obtain government subsidies and social reputation. At the same time, when "no production of new energy vehicles" is implemented, fines such as environmental taxes will be imposed. For consumers, there are two strategies to choose from: "consume green products" and "no consumption of green products", with selection ratios of z and 1-z respectively. Among them, when consumers choose the strategy of "green consumption", some additional payments will be incurred, but certain government subsidies and environmental utilities will be obtained. The x, y, and z mentioned above all change over time, and their value range is [0,1].

[0148] The government-related parameters are: S is the regulatory cost; F is the fine for passenger car manufacturers that fail to meet fuel consumption standards or new energy vehicle standards; companies that produce and sell new energy vehicles are subsidized with a coefficient α, and the value range of α is (0,1). Similarly, consumers who consume and use new energy vehicles are subsidized with a coefficient β based on the input cost, and the value range of β is the same as α; G is the environmental benefit obtained by the government from the production and consumption of new energy vehicles; L is the loss of credibility when the government does not supervise the production of fuel vehicles by automobile companies.

[0149] The relevant parameters of passenger car companies are: C is the cost when new energy vehicles are not produced, and R is the benefit; C1 is the additional cost invested in the production of new energy vehicles; R1 is the additional benefit obtained by the company when the government and consumer strategy group is (regulation, consumption of green products), which is the increase in profits caused by low-carbon consumption; R2 is the additional benefit obtained by the company when the government and consumer strategy group is (no regulation, consumption of green products), including the increase in profits caused by low-carbon consumption and the improvement of corporate reputation brought about by active green production, so 0<R1<R2.

[0150] Consumer-related parameters are: P is the expenditure when no green consumption is carried out, and U is the benefit; U1 is the additional utility obtained by consumers when consuming green products, such as environmental protection; P1 is the additional cost (price difference) that consumers need to pay when consuming green products when the enterprise provides new energy vehicles; P2 is the additional information and conversion costs and time costs that consumers need to pay when consuming green products when the enterprise does not provide new energy vehicles.

[0151] 2. Establishment of evolutionary game model

[0152] According to the above model assumptions and set parameters, the following payment matrix can be obtained, see Table 1.

[0153] Table 1 Government, enterprise and consumer payment matrix

[0154]

[0155] According to Table 1, we can get the expected benefit U of the government when choosing regulation: x1 ,

[0156]

[0157] and the expected benefit U of the government when it chooses not to regulate x2 ,

[0158] U x2 =yzG+y(1-z)G+(1-y)z(-L)+(1-y)(1-z)(-L) (2)

[0159] So the average government revenue is for:

[0160]

[0161] According to the replication dynamics formula of evolutionary game, the replication dynamics equation of government decision-making can be obtained:

[0162]

[0163] when When , no matter what value x takes, F(x) = 0, and the government's decision remains stable; when When F′(x)| x＝0 <0, F′(x)| x＝1 >0, then x=0 is the equilibrium point; when When F′(x)| x＝0 >0,F′(x)| x＝1 <0, at this time x=1 is the equilibrium point.

[0164] Similarly, the expected revenue of a passenger car company is U y1 , U y2 , average revenue And the replicated dynamic equation F(y) is shown below:

[0165]

[0166] U y2 =x(RCF)+(1-x)(RC) (6)

[0167]

[0168] when When , no matter what value y takes, F(y) = 0, and the decision of the passenger car company remains stable; when When F′(y)| y＝0 <0, F′(y)| y＝1 >0, then y=0 is the equilibrium point; when When F′(y)| y＝0 >0,F′(y)| y＝1 <0, at this time y=1 is the equilibrium point.

[0169] Similarly, we can get the consumer's expected benefit U z1 , U z2 , average revenue And the replicated dynamic equation F(z) is shown below:

[0170]

[0171] U z2 =xy(UP)+x(1-y)(UP)+(1-x)y(UP)+(1-x)(1-y)(UP) (10)

[0172]

[0173] when When , no matter what value z takes, F(z) = 0, and the consumer's decision remains stable; when When F′(z)| z＝0 <0,F′(z)| z＝1 >0, then z=0 is the equilibrium point; when When F′(z)| z＝0 >0,F′(z)| z＝1 <0, at this time z=1 is the equilibrium point.

[0174] Specifically, Figure 2(a)-Figure 2(c) It is the influence curve of the initial values ​​of y and z on the evolution of x. It can be observed that the production decision of enterprises will directly affect the equilibrium decision of whether the government regulates or not, but with the mutual game between the government, enterprises and consumers, the government will eventually believe that it is no longer necessary to regulate the new energy vehicle market.

[0175] Figure 3(a)-Figure 3(c) It is the influence curve of the initial values ​​of x and z on the evolution of y. It can be observed that if we want enterprises to consciously provide new energy vehicles, promoting consumers' "green consumption" is the top priority.

[0176] Figure 4(a)-Figure 4(c) It is the influence curve of the initial values ​​of x and z on the evolution of y.

[0177] 3. Stability analysis

[0178] Let F(x) = 0, F(y) = 0, F(z) = 0, and we can get 9 equilibrium points that make the government, passenger car companies and consumers all reach a stable state: A1(0,0,0), A2(1,0,0), A3(0,1,0), A4(0,0,1), A5(1,1,0), A6(1,0,1), A7(0,1,1), A8(1,1,1), A9(x * ,y * ,z * ). Among them, A9(x * ,y * ,z * ) is an internal equilibrium point, so it is in a non-asymptotically stable state. The asymptotic stability of equilibrium points A1~A8 can be determined based on the Jacobian matrix local stability analysis method.

[0179] The Jacobian matrix J corresponding to the evolutionary game model described in the embodiment of the present invention is given below:

[0180]

[0181] Among them, a 11 =(1-2x)[yzβP2-y(αC1+F+L)-zβ(P1+P2)+F+LS];

[0182] a 12 =x(1-x)(zβP2-αC1-FL);

[0183] a 13 =x(1-x)(yβP2-βP1-βP2);

[0184] a 21 =y(1-y)[z(R1-R2)+αC1+F];

[0185] a 22 =(1-2y)[xz(R1-R2)+x(αC1+F)+zR2-C1];

[0186] a 23 =y(1-y)[x(R1-R2)+R2];

[0187] a 31 =z(1-z)(-yβP2+βP1+βP2);

[0188] a 32 =z(1-z)(-xβP2+P2);

[0189] a 33=(1-2z)[xβ(P1+P2)-xyβP2+yP2+U1-P1-P2].

[0190] According to the Lyapunov law, when the eigenvalues ​​of the Jacobian matrix J corresponding to the local equilibrium point are all negative, the equilibrium point is asymptotically stable, and the strategy group represented by this point is called an evolutionary stable strategy (ESS); when the eigenvalues ​​of the Jacobian matrix J are all positive, the equilibrium point is an unstable point; when one or two of the eigenvalues ​​of J are greater than 0, the equilibrium point is a saddle point.

[0191] The eigenvalues ​​of the Jacobian matrix J at the eight equilibrium points and their positivity are calculated and given below, see Table 2.

[0192] Table 2 Equilibrium point stability analysis

[0193]

[0194] The symbols "+", "-", and "*" in brackets in Table 2 represent positive and negative eigenvalues, respectively. The positivity of the eigenvalues ​​is to be determined (depending on the specific parameter values). From the results shown in Table 2, it can be seen that A1, A2, A4, A6, and A7 may be evolutionary stable strategies, among which the strategies of consumers A4, A6, and A7 are to support green consumption, which is the ideal market state to be studied in the embodiment of the present invention.

[0195] According to Table 2, if A4(0,0,1) is to become an evolutionary stable strategy, it needs to satisfy F+LS-βP1-βP2<0, R2<C1 and P1+P2-U1<0. For the government, F+LS-βP1-βP2<0 means that the government needs to reduce the fine F and the loss of credibility L when not supervising, while increasing the supervision cost S, which is obviously unreasonable and difficult to implement; for enterprises, R2<C1 means that enterprises need to reduce the profit R2 when (not supervising, consuming green products) and increase the additional cost C1 when producing new energy vehicles, which is contrary to common sense like the government. Therefore, it can be considered that as long as the actions of the government and enterprises are in line with common sense, that is, pursuing cost minimization and benefit maximization, then A4(0,0,1) cannot become an evolutionary stable strategy.

[0196] Similarly, if A6(1,0,1) is to become an evolutionary stable strategy, it needs to satisfy βP1+βP2+SFL<0, R1+F+αC1-C1<0 and P1+P2-βP1-βP2-U1<0. At this time, for the enterprise, it needs to reduce the additional benefit R1 when (regulating, consuming green products) and increase the additional cost C1 when producing new energy vehicles, which is obviously unreasonable. Therefore, when the enterprise pursues cost minimization and profit maximization, A6(1,0,1) cannot become an evolutionary stable strategy.

[0197] Finally, if A7(0,1,1) is to become an evolutionary stable strategy, it needs to satisfy C1-R2<0 and P1-U1<0. At this time, for passenger car companies, it is necessary to reduce the additional cost C1 when producing new energy vehicles, while increasing the additional benefit R2 when (no supervision, consumption of green products), which is in line with the nature of companies pursuing cost minimization and profit maximization; for consumers, P1-U1<0 means that the price difference and use cost between new energy vehicles and traditional fuel vehicles should be as low as possible, while supporting the environmental benefits brought by green consumption should be as large as possible, which is in line with the psychology of the public in reality. It can be seen that it is reasonable and feasible for A7(0,1,1) to become an evolutionary stable strategy.

[0198] Specifically, Figure 5(a)-Figure 5(g) is the evolution path of the three-party pure strategy group. It can be observed that all pure strategy groups except A7(0,1,1) are not asymptotically stable and will deviate from the original equilibrium state due to slight changes. The final evolutionary result of all pure strategy groups that deviate from the original equilibrium state is A7(0,1,1), that is, under a given initial state, the system dynamics model has a unique evolutionary stable strategy A7(0,1,1), which means that the government does not need to regulate, car companies choose to produce new energy vehicles, and consumers consume green products. This result is consistent with the results of the evolutionary game model analysis and can verify each other.

[0199] 4. Build a system dynamics model

[0200] The above analysis has obtained the asymptotic stability of the three-party evolutionary game model of the government, passenger car companies and consumers, but it cannot intuitively show the evolution process of the evolutionary game. In order to better describe the process of the interaction between the government, automobile companies and consumers to influence their respective decisions, the embodiment of the present invention uses the system dynamics method to visualize this process, and by changing the relevant parameters, analyzes the specific factors and their directions of action that affect the production and consumption of new energy vehicles.

[0201] According to the above evolutionary game model and analysis, the system should include three subsystems: government, passenger car enterprises and consumers. Vensim PLE is used to construct a system dynamics model. Among them, the government regulation ratio, the production ratio of new energy vehicles and the consumption ratio of green products are all set as level variables, indicating the cumulative amount of the strategy ratios of each subject; the regulatory change rate, the production change rate of new energy vehicles and the green consumption change rate are rate variables, which can make the three level variables increase or decrease continuously over time; the rest are auxiliary variables. The functional relationship between each variable can be given by the evolutionary game model constructed in the previous section.

[0202] Specifically, Figure 6(a)-Figure 6(c)It is the influence curve of the change of the initial value of P1 on the strategy evolution. It can be observed that the price difference P1 between fuel vehicles and new energy vehicles will not have a decisive impact on the government's regulatory decision within a certain range, and the government will eventually choose "no regulation". A noteworthy detail is that the speed at which the government regulatory ratio x evolves to 0 does not always decrease or increase with the increase of P1. The price difference P1 is an important factor affecting the decision-making of enterprises and consumers, and should be controlled within a reasonable range, otherwise excessive price differences will discourage consumers from green products. It is easy to find that when the premium payment ratio of consumers for new energy vehicles is 27.27%, the government can let go of the supervision of the green product market at the fastest speed, and enterprises and consumers will also choose to consciously enter the green product market at a faster speed.

[0203] Figure 7(a)-Figure 7(c) It is the influence curve of the change of the initial value of U1 on the strategy evolution. It can be observed that the government should be committed to improving the construction of green and low-carbon facilities, such as the development and improvement of the clean power generation system. Secondly, it should enhance consumers' overall green environmental awareness through policy publicity and popularization education, and vigorously publicize the environmental benefits brought by green products, so that consumers' psychological expectations of their own green and low-carbon consumption behaviors will gradually increase.

[0204] The embodiment of the present invention considers the limited rationality of all three participants in the new energy vehicle market - the government, manufacturers and consumers, and combines the actual relevant policies of the government to build an evolutionary game model to provide theoretical support for the government to formulate policies and develop the new energy vehicle market. The system dynamics method is used in combination with actual data to dynamically describe and analyze the policy evolution process.

[0205] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0206] The above description of the disclosed embodiments enables professionals and technicians in the field to implement or use the present invention. Various modifications to these embodiments will be apparent to professionals and technicians in the field, and the general principles defined in the embodiments of the present invention can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown in the embodiments of the present invention, but will conform to the widest range consistent with the principles and novel features disclosed in the embodiments of the present invention.

Claims

1. A new energy market dynamic evolution method based on game decision-making, characterized in that: include: Based on the interactive relationship and interest relationship among producers, consumers and supervisors, a three-party evolutionary game model of the new energy market is established; Based on the three-party evolutionary game model, a three-dimensional replication dynamic equation set is established for the expected benefits of the three parties; The equilibrium point is obtained based on the three-dimensional replication dynamic equations, and stability analysis is performed to obtain the evolutionary stability strategy; Using the system dynamics method, the dynamic evolution process of the new energy market is drawn based on the three-party evolutionary game model.

2. The method for dynamic evolution of new energy market based on game decision-making according to claim 1 is characterized in that: Also includes: Combining the convergence path of dynamic evolution and the evolutionary stabilization strategy, the impact of decision variables and environmental variables on the new energy market is analyzed.

3. The method for dynamic evolution of new energy market based on game decision-making according to claim 1 is characterized in that: A three-dimensional replication dynamic equation system is established for the expected returns of the three parties: The replication dynamics equation of the supervisor decision is expressed as: Among them, U x1 represents the expected benefit of the supervisor when choosing a supervision strategy, U x2 represents the expected benefit of the supervisor when choosing the non-supervision strategy, represents the average benefit of the supervisor, x represents the selection ratio of the supervision strategy, 1-x represents the selection ratio of the non-supervision strategy, y represents the selection ratio of the production strategy, z represents the selection ratio of the consumption strategy, α represents the subsidy coefficient of the supervisor to the producer, β represents the subsidy coefficient of the supervisor to the consumer, S represents the supervision cost, F represents the fine on the producer, and L represents the loss when the supervisor does not supervise; P1 represents the additional cost that consumers need to pay when consuming green products when producers provide new energy products; P2 represents the additional information and conversion costs and time costs that consumers need to pay when consuming green products when producers do not provide new energy products; The replication dynamics equation for producer decision is expressed as: in, represents the average revenue of producers, C1 is the additional cost of producing new energy products; R1 is the additional revenue obtained by producers when supervisors and consumers choose supervision strategy and consumption strategy respectively; R2 is the additional revenue obtained by producers when supervisors and consumers choose no supervision strategy and no consumption strategy respectively; The replication dynamic equation of consumer decision making is expressed as: in, It represents the average revenue of producers.

4. The method for dynamic evolution of new energy market based on game decision-making according to claim 3 is characterized in that: According to the expected benefits of the supervisor when choosing the supervision strategy and the expected benefits of the non-supervision strategy, the average benefit of the supervisor is: Among them, U x1 represents the expected benefit of the supervisor when choosing a supervision strategy, U x2 represents the expected return of the supervisor when choosing the unsupervised strategy, x represents the selection ratio of the supervised strategy, and 1-x represents the selection ratio of the unsupervised strategy; According to the expected profit of producers when choosing production strategy and the expected profit when not choosing production strategy, the average profit of producers is: Among them, U y1 represents the expected profit of the producer when choosing a production strategy, U y2 represents the expected profit of the producer when choosing the non-production strategy, y represents the selection ratio of the production strategy, and 1-y represents the selection ratio of the non-production strategy; According to the expected benefits of consumers when choosing consumption strategies and the expected benefits when not choosing consumption strategies, the average benefits of consumers are: Among them, U z1 represents the expected benefit of consumers when choosing consumption strategies, U z2 represents the expected benefit of the consumer when choosing the non-consumption strategy, z represents the selection ratio of the consumption strategy, and 1-z represents the selection ratio of the non-consumption strategy.

5. The method for dynamic evolution of new energy market based on game decision-making according to claim 3 is characterized in that: Let F(x) = 0, F(y) = 0, F(z) = 0, and we can get 9 equilibrium points that make the supervisor, producer, and consumer all reach a stable state: A1(0,0,0), A2(1,0,0), A3(0,1,0), A4(0,0,1), A5(1,1,0), A6(1,0,1), A7(0,1,1), A8(1,1,1), A9(x * ,y * ,z * ); Among them, A9(x * ,y * ,z * ) is the internal equilibrium point, which is in a non-asymptotically stable state, and A1~A8 are local equilibrium points, which are in an asymptotically stable state; The Jacobian matrix is ​​used to analyze the stability of each local equilibrium point.

6. The method for dynamic evolution of new energy market based on game decision-making according to claim 5 is characterized in that: When the eigenvalues ​​of the Jacobian matrix corresponding to a local equilibrium point are all negative, the local equilibrium point is asymptotically stable, and the strategy group represented by the local equilibrium point is called an evolutionary stable strategy; When the eigenvalues ​​of the Jacobian matrix corresponding to the local equilibrium point are all positive, the local equilibrium point is an unstable point; When one or two eigenvalues ​​of the Jacobian matrix corresponding to a local equilibrium point are greater than 0, the local equilibrium point is a saddle point.

7. The method for dynamic evolution of new energy market based on game decision-making according to claim 3 is characterized in that: when When , no matter what value x takes, F(x) = 0, and the supervisor's decision remains stable; when When F′(x)| x＝0 <0, F′(x)| x＝1 >0, then x=0 is the equilibrium point; when When F′(x)| x＝0 >0,F′(x)| x＝1 <0, at this time x=1 is the equilibrium point; when When , no matter what value y takes, F(y) = 0, and the producer's decision remains stable; when When F′(y)| y＝0 <0, F′(y)| y＝1 >0, then y=0 is the equilibrium point; when When F′(y)| y＝0 >0,F′(y)| y＝1 <0, at this time y = 1 is the equilibrium point; when When , no matter what value z takes, F(z) = 0, and the consumer's decision remains stable; when When F′(z)| z＝0 <0,F′(z)| z＝1 >0, then z=0 is the equilibrium point; when When F′(z)| z＝0 >0,F′(z)| z＝1 <0, at this time z=1 is the equilibrium point.

8. The method for dynamic evolution of new energy market based on game decision-making according to claim 5 is characterized in that: The Jacobian matrix is ​​expressed as: in, a 11 =(1-2x)[yzβP2-y(αC1+F+L)-zβ(P1+P2)+F+L-S]; a 12 =x(1-x)(zβP2-αC1-F-L); a 13 =x(1-x)(yβP2-βP1-βP2); and 21 =y(1-y)[z(R1-R2)+αC1+F]; a 22 =(1-2y)[xz(R1-R2)+x(αC1+F)+zR2-C1]; a 23 =y(1-y)[x(R1-R2)+R2]; a 31 =z(1-z)(-yβP2+βP1+βP2); and 32 =z(1-z)(-xβP2+P2); a 33 =(1-2z)[xβ(P1+P2)-xyβP2+yP2+U1-P1-P2]。 9. A new energy market dynamic evolution system based on game decision-making, applying a new energy market dynamic evolution method based on game decision-making as described in any one of claims 1 to 8, characterized in that: include: Model building module, which is used to establish a three-party evolutionary game model of the new energy market based on the interactive relationship and interest relationship among producers, consumers and supervisors; An equation group establishment module, used for establishing a three-dimensional replication dynamic equation group for the expected benefits of the three parties based on the three-party evolutionary game model; The stability analysis module is used to obtain the equilibrium point based on the three-dimensional replication dynamic equations, and to perform stability analysis to obtain the evolutionary stability strategy; The dynamic evolution module is used to draw the dynamic evolution process of the new energy market according to the three-party evolutionary game model by using the system dynamics method.

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