An electric vehicle charging regulation method and system based on comprehensive pricing

Abstract

The application relates to an electric vehicle charging regulation method and system based on comprehensive pricing, which comprises the following steps: constructing a comprehensive pricing model among multiple electric vehicle charging stations; analyzing the components of the charging cost of the electric vehicle; classifying the components according to the cost, and determining the electric vehicle charging station selection standard of the electric vehicle user; analyzing the interaction among multiple electric vehicle charging stations with selfishness in a market sharing environment by using the game theory, obtaining the equilibrium condition of the pricing and profit of the multiple electric vehicle charging stations; finding a suitable pricing model of the multiple electric vehicle charging stations participating in competition in the market sharing environment based on the Hotelling game mode; and regulating each electric vehicle to select the corresponding electric vehicle charging station for charging according to the suitable pricing model. The energy demand and travel cost of the electric vehicle user are considered, and meanwhile, the electric vehicle charging stations of the numerous charging service suppliers are also conducive to obtaining more profits in the charging market.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power system demand response, and particularly relates to an electric vehicle charging regulation method and system based on comprehensive pricing. BACKGROUND

[0002] Greenhouse gas emissions have long been a major concern of society, and the total greenhouse gas emissions of traditional fuel transportation are relatively large. Considering environmental benefits and the development of battery technology, electric vehicles (EVs) are increasingly popular among various stakeholders. However, due to consumer concerns about the lack of electric vehicle charging infrastructure, the market penetration rate of electric vehicles is limited. In order to achieve a larger share of electric vehicles in the transportation industry, the charging infrastructure must develop at a faster rate to meet the growing charging needs of electric vehicles. The emerging charging market will prompt competitive charging service providers to invest in deploying charging stations in the hope of generating greater profits in the potential common market.

[0003] In actual scenarios, drivers are very familiar with the energy demand patterns of electric vehicles, and due to the anxiety caused by the rapid changes in charging prices of charging stations, users of electric vehicles do not trust charging stations, which leads users of electric vehicles to only choose charging stations close to themselves for charging without considering the charging expenses of users, which is not conducive to many charging service providers to obtain more profits in the charging market. SUMMARY

[0004] In order to make up for the defects of the prior art, the application provides an electric vehicle charging regulation method and system based on comprehensive pricing.

[0005] In order to solve the above technical problems, the technical scheme adopted by the application is:

[0006] In a first aspect, an electric vehicle charging regulation method based on comprehensive pricing is provided, comprising:

[0007] A comprehensive pricing model between a plurality of electric vehicle charging stations is constructed, and the target constraint condition of the comprehensive pricing model is that the charging cost of the electric vehicle is minimized, and the profit of the electric vehicle charging station charging the electric vehicle with a service fee in addition to the energy cost is maximized;

[0008] The components of the charging cost of the electric vehicle are analyzed;

[0009] The components are classified by cost, and the electric vehicle charging station selection standard of the electric vehicle user is determined according to the classification result of the cost classification;

[0010] The interaction between a plurality of self-interested electric vehicle charging stations in a market sharing environment is analyzed using game theory to obtain the equilibrium condition of the pricing and profit of the plurality of electric vehicle charging stations;

[0011] Finding a suitable pricing model for multiple electric vehicle charging stations participating in competition in a market sharing environment based on Hotelling game mode;

[0012] Regulating each electric vehicle to select a corresponding electric vehicle charging station for charging according to the suitable pricing model.

[0013] Further, constructing a comprehensive pricing model among multiple electric vehicle charging stations, including:

[0014] Obtaining multiple electric vehicle charging stations located at different positions along a road with a length L;

[0015] Modeling the projection of electric vehicles on the highway as uniformly distributed along the length L, obtaining the uniform probability density function of electric vehicles as ;

[0016] Without loss of generality, the main road is along the x-axis of the Cartesian coordinate system;

[0017] The set of multiple electric vehicle charging stations is , the charging service provider is located at a distance of , so that , and the electric vehicle is ;

[0018] The charging energy demand of the electric vehicle is modeled as a random variable , obtaining the uniform probability density function of energy demand as ; all electric vehicle charging stations are connected to the power grid;

[0019] Setting the target constraint condition as the minimum charging cost of the electric vehicle , and the maximum profit of the electric vehicle charging station charging the electric vehicle except for the energy cost, constructing a comprehensive pricing model among multiple electric vehicle charging stations.

[0020] Further, analyzing the components of the charging cost of the electric vehicle, including:

[0021] Analyzing the energy cost of the electric vehicle as , indicating the energy cost component provided by the electric vehicle charging station O n , indicating the unit energy cost generated by the electric vehicle charging station O n ;

[0022] Analyzing the service cost of the electric vehicle as , represents the electric vehicle charging station O n a service cost component, represents the electric vehicle charging station O n a fixed cost per unit of energy, is a fixed value;

[0023] analyzing the travel cost of the electric vehicle is , represents the electric vehicle the travel energy cost consumed by the electric vehicle to reach the electric vehicle charging station O n , represents the electric vehicle the unit distance travel cost of the electric vehicle, represents the electric vehicle the distance between the electric vehicle and the electric vehicle charging station O n , is a random variable subject to uniform distribution;

[0024] analyzing the waiting cost of the electric vehicle is , represents the electric vehicle the effective waiting cost of the electric vehicle queuing at the electric vehicle charging station O n , represents the electric vehicle the unit time waiting cost of the electric vehicle, represents the electric vehicle charging station O n the waiting time, is a random variable subject to exponential distribution, and the expected waiting time of the electric vehicle charging station O n is ;

[0025] analyzing the effective charging cost of the electric vehicle charging at the electric vehicle charging station O n is ;

[0026] , wherein the electric vehicle is located at , and the distance from the electric vehicle charging station O n is ;

[0027] The electric vehicle choosing the electric vehicle charging station O i for charging at compared to choosing the electric vehicle charging station O j for charging, the additional benefit is:

[0028] .

[0029] Further, the components are classified according to the cost classification, and the electric vehicle charging station selection criteria of the electric vehicle user are determined according to the classification results of the cost classification, including:

[0030] The energy cost, service cost, travel cost and effective charging cost are classified as travel cost;

[0031] According to the travel cost and the waiting cost, the electric vehicle charging station selection criteria of the electric vehicle user is the lowest travel cost or the shortest waiting time.

[0032] Further, the interaction between multiple selfish electric vehicle charging stations in a market sharing environment is analyzed by using game theory, and the equilibrium conditions of the pricing and profits of multiple electric vehicle charging stations are obtained, including:

[0033] The electric vehicle is modeled as a selfish node, and the electric vehicle charging station selection criteria is set to the lowest travel cost;

[0034] The expected profit of the electric vehicle charging station is expressed as: , wherein, is the expected profit of the electric vehicle charging station On, represents the expectation, represents the number of electric vehicles positioned within a unit distance, represents the charging pile terminal cost of the electric vehicle charging station O n The length of the captured section is defined as the demand length; represents the charging pile terminal cost of the electric vehicle charging station O n ;

[0035] The equilibrium conditions of the pricing and profits of multiple non-cooperative electric vehicle charging stations are obtained by using game theory; considering the competitive relationship between N electric vehicle charging stations in a market sharing environment, the expected profit of each electric vehicle charging station is maximized, and the existence of Nash equilibrium NE condition is proved for the game model considering non-cooperative game between N electric vehicle charging stations.

[0036] In the second aspect, a comprehensive pricing-based electric vehicle charging regulation system is provided, including:

[0037] A model construction module is configured to construct a comprehensive pricing model between multiple electric vehicle charging stations, and the target constraint condition of the comprehensive pricing model is to minimize the charging cost of the electric vehicle and maximize the profit of the electric vehicle charging station charging the electric vehicle except for the energy cost;

[0038] A charging cost analysis module is configured to analyze the components of the charging cost of the electric vehicle;

[0039] selecting criteria module, configured to classify the components according to cost, and determine the selection criteria of the electric vehicle charging station of the electric vehicle user according to the classification result of the cost classification;

[0040] game theory analysis module, configured to analyze the interaction between multiple self-interested electric vehicle charging stations in a market sharing environment by using game theory, to obtain the equilibrium condition of pricing and profit of the multiple electric vehicle charging stations;

[0041] pricing module, configured to find a suitable pricing model of multiple electric vehicle charging stations participating in competition in a market sharing environment based on a Hotelling game mode;

[0042] charging regulation module, configured to regulate each electric vehicle to select a corresponding electric vehicle charging station for charging according to the suitable pricing model.

[0043] Further,

[0044] model construction module, specifically configured to obtain multiple electric vehicle charging stations located at different positions along a road with a length L; model the projection of the electric vehicle on the highway as being uniformly distributed along the length L, to obtain an electric vehicle uniform probability density function as ; without loss of generality, the main road is along the x-axis of the Cartesian coordinate system; the set of multiple electric vehicle charging stations is , the charging service provider is located at a distance of , so that , the electric vehicle is ; the charging energy demand of the electric vehicle is modeled as a random variable , to obtain an energy demand uniform probability density function as ; all electric vehicle charging stations are connected to the power grid; the target constraint condition is set as the minimum charging cost of the electric vehicle , and the maximum profit of the electric vehicle charging station charging the electric vehicle except for the energy cost, to construct a comprehensive pricing model between the multiple electric vehicle charging stations.

[0045] Further,

[0046] charging cost analysis module, specifically configured to analyze the energy cost of the electric vehicle as , , wherein n represents an energy cost component provided by the electric vehicle charging station O n , represents the unit energy cost generated by the electric vehicle charging station O n ,

[0047] Analyzing Electric Vehicles The service cost is , Indicates electric vehicle charging station O n The cost component of the services provided, Indicates electric vehicle charging station O n The fixed cost per unit of energy, is a fixed value;

[0048] Analyzing Electric Vehicles The travel cost of users is , Indicates electric vehicles Arrival at Electric Vehicle Charging Station O n The energy cost of driving, Indicates electric vehicles The unit distance travel cost, Indicates electric vehicles With electric car charging station O n The distance between is a random variable that obeys a uniform distribution;

[0049] Analyzing Electric Vehicles The waiting cost is , Indicates electric vehicles At the electric vehicle charging station n The effective waiting cost of waiting in line, Indicates electric vehicles The waiting cost per unit time is Indicates electric vehicle charging station O n The waiting time, is a random variable that obeys exponential distribution, and the electric vehicle charging station O n The expected waiting time is ;

[0050] Analyzing Electric Vehicles At the electric vehicle charging station n The effective charging cost of charging is ;

[0051] , among which electric vehicles lie in , 0 away from the electric vehicle charging station n The distance is ;

[0052] electric vehicles exist Choose an electric vehicle charging station iCompare and choose an electric vehicle charging station j For charging, the extra income is:

[0053] .

[0054] Further,

[0055] The selection standard module is specifically used to classify energy cost, service cost, travel expense cost and effective charging cost into travel cost; based on travel cost and waiting cost, the electric vehicle charging station selection standard for electric vehicle users is determined to be the lowest travel cost or the shortest waiting time.

[0056] Further,

[0057] A game theory analysis module, specifically used to model electric vehicles as self-interested nodes and set the electric vehicle charging station selection criteria to minimize travel costs;

[0058] The expected profit of an electric vehicle charging station is expressed as: ,in, Charging station for electric vehicles n The expected profit, Express expectations, Indicates the number of electric vehicles located within a unit distance, Indicates electric vehicle charging station O n The length segment captured is defined as the required length; Indicates electric vehicle charging station O n Charging pile terminal cost;

[0059] Game theory is used to find the equilibrium conditions for pricing and profits of multiple non-cooperative electric vehicle charging stations; considering the competitive relationship between N electric vehicle charging stations in a price war under the same market sharing environment, the expected profit of each electric vehicle charging station is maximized. For the game model considering the non-cooperative game between N electric vehicle charging stations, the existence of the Nash equilibrium NE condition is proved.

[0060] The beneficial effects achieved by the present invention are:

[0061] The appropriate pricing model of the present invention does not require real-time information about electric vehicles. Instead, by presetting parameters such as the energy demand and expected travel cost of electric vehicles, charging plans can be formulated more quickly.

[0062] Applicable to evolving market situations, if a new charging station service provider wishes to establish its EV charging stations amidst existing competition to capitalize on the growing demand for charging in the market, it should estimate a priori the expected profits in NE conditions at its possible locations using the latest information on existing market conditions;

[0063] The electric vehicle charging station is beneficial to many charging service providers to obtain more profits in the charging market while considering the energy demand and travel cost of the electric vehicle user. BRIEF DESCRIPTION OF DRAWINGS

[0064] Figure 1 A flowchart of the electric vehicle charging regulation method based on comprehensive pricing of the present application;

[0065] Figure 2 A structural diagram of the electric vehicle charging regulation system based on comprehensive pricing of the present application. DETAILED DESCRIPTION

[0066] The present application will be further described below in conjunction with the drawings. The following examples are only used to more clearly illustrate the technical solutions of the present application, and cannot be used to limit the protection scope of the present application.

[0067] As shown in the drawings, the embodiment of the present application provides an electric vehicle charging regulation method based on comprehensive pricing, comprising: Figure 1

[0068] 101, a comprehensive pricing model between a plurality of electric vehicle charging stations is constructed, and the target constraint condition of the comprehensive pricing model is that the charging cost of the electric vehicle is minimum, and the profit of the service fee collected by the electric vehicle charging station from the electric vehicle in addition to the energy cost is maximum;

[0069] Specifically, a plurality of electric vehicle charging stations are located at different positions along a road with a length L. The road is generally a main road or a highway, and the electric vehicles are dispersed in the urban or rural areas with good traffic near the main road or the highway;

[0070] The projection of the electric vehicle on the highway is modeled as a uniform distribution along the length L, and the uniform probability density function of the electric vehicle is obtained as ;

[0071] Without loss of generality, the main road is along the x-axis of the Cartesian coordinate system;

[0072] The set of the plurality of electric vehicle charging stations is , the charging service provider is located at a distance of , so that , the electric vehicle is ;

[0073] The charging energy demand of the electric vehicle is modeled as a random variable , and the uniform probability density function of the energy demand is obtained as ; all the electric vehicle charging stations are connected to the power grid; ​

[0074] The target constraint condition is set as the minimum charging cost of the electric vehicle , and the profit of the electric vehicle charging station is maximized by charging service fees in addition to energy costs, and a comprehensive pricing model between multiple electric vehicle charging stations is constructed.

[0075] 102, analyzing the components of the charging cost of the electric vehicle;

[0076] analyzing the energy cost of the electric vehicle , , representing the energy cost component provided by the electric vehicle charging station O n , representing the unit energy cost generated by the electric vehicle charging station O n ;

[0077] analyzing the service cost of the electric vehicle , , representing the service cost component provided by the electric vehicle charging station O n , representing the fixed cost per unit energy of the electric vehicle charging station O n , is a fixed value;

[0078] analyzing the travel cost of the user of the electric vehicle , , representing the driving energy cost consumed by the electric vehicle to reach the electric vehicle charging station O n , representing the unit distance travel cost of the electric vehicle , representing the distance between the electric vehicle and the electric vehicle charging station O n , is a random variable subject to uniform distribution;

[0079] analyzing the waiting cost of the electric vehicle , , representing the effective waiting cost of the electric vehicle in the queue at the electric vehicle charging station O n , representing the unit time waiting cost of the electric vehicle , representing the waiting time of the electric vehicle charging station O n , ​For the random variable obeying exponential distribution, the expected waiting time of electric vehicle charging station O n is ;

[0080] The effective charging cost of electric vehicle charging at electric vehicle charging station O n is ;

[0081] , wherein the electric vehicle is located at , and the distance from the electric vehicle charging station O n is ;

[0082] The electric vehicle chooses the electric vehicle charging station O i to charge at compared to choosing the electric vehicle charging station O j to charge, the additional income is:

[0083] .

[0084] 103, cost classification is performed on the components, and the electric vehicle charging station selection standard of the electric vehicle user is determined according to the classification result of the cost classification;

[0085] The energy cost , the service cost , the travel expense cost and the effective charging cost are classified as travel cost;

[0086] According to the travel cost and the waiting cost , the electric vehicle charging station selection standard of the electric vehicle user is that the travel cost is the lowest or the waiting time is the shortest; the two selection standards have different focuses, the travel cost being the lowest can reduce the user's expenses, and the waiting time being the shortest can reduce the charging queue waiting time.

[0087] 104, the interaction among multiple selfish electric vehicle charging stations in a market sharing environment is analyzed by using game theory, and the equilibrium condition of the pricing and profit of multiple electric vehicle charging stations is obtained;

[0088] The electric vehicle is modeled as a selfish node, and the selection mode of electric vehicle drivers in a common market is investigated, assuming that all electric vehicle drivers know the expected travel cost, the expected waiting cost and the electric vehicle density, etc. Common market parameters, and setting the electric vehicle charging station selection standard as the lowest travel cost.

[0089] The expected profit of an electric vehicle charging station is expressed as: ,in, Charging station for electric vehicles n The expected profit, Express expectations, Indicates the number of electric vehicles located within a unit distance, Indicates electric vehicle charging station O n The length segment captured is defined as the required length; Indicates electric vehicle charging station O n The terminal cost of charging piles; electric vehicle charging stations need to regularly exchange their charging price components ( , ) and expected waiting time To achieve the generalized Nash equilibrium point NE;

[0090] Game theory is used to find the equilibrium conditions for pricing and profits of multiple non-cooperative electric vehicle charging stations; considering the competitive relationship between N electric vehicle charging stations in a price war under the same market sharing environment, the expected profit of each electric vehicle charging station is maximized. For the game model considering the non-cooperative game between N electric vehicle charging stations, the existence of the Nash equilibrium NE condition is proved.

[0091] 105. Finding a suitable pricing model for multiple competing electric vehicle charging stations in a market sharing environment based on Hotelling game approach;

[0092] According to the scenario described in step 101 above, the electric vehicle charging station O n Placed on a road of length L Location, where , modeled as a static Hotelling's game, with elements including players, actions, and utilities as follows:

[0093] Participants: N electric vehicle charging stations are participants, with O n express.

[0094] Action: By participant O n Price selection made , Participant O n Action at NE express;

[0095] Utilities: Use Indicates that participant O n The effect Defined as O n The expected profit of participant O n The utility on NE is denoted as ;

[0096] Consider the non-cooperative case, all participants O n Compete in price war to maximize profit while sharing the common market; consider game participants O n Make decisions at the beginning of the game, analyze the existence of generalized Nash equilibrium NE in the proposed game model, and the network element is a profile So that for each participant O n There exists ;

[0097] Assume that there is a point sk between participant O n And participant O n+1 , so that The charging cost of electric vehicles in O n And O n+1 is equal, define the sk point as the critical point (CP), CP is the decision point of electric vehicles related to adjacent electric vehicle charging stations;

[0098] Define the electric vehicle Find the problem of decision point:

[0099] Between adjacent participants O n And O n+1 , find the closed form of the solution expressed as According to different cost components, it is given in (1) as follows:

[0100] (1) Define the critical point Of adjacent participants O n And O n+1 , n∈{1,2,.. n−1}, where electric vehicle Has energy demand And unit distance travel cost , expressed as:

[0101] ,

[0102] Among them, , Indicates the unit energy cost generated by electric vehicle charging station O n , And Are the waiting time of O n And O n+1 , Indicates the unit time waiting cost of electric vehicle ;

[0103] (2) Under the condition of market sharing, located between two adjacent critical points and between two adjacent critical points of electric vehicle charging stations O n is the most cost-effective among all the schemes, where is the adjacent electric vehicle charging station O n and O n+1 are the critical points, of electric vehicle charging stations O n-1 and O n are the corresponding critical points;

[0104] (3) Under the market sharing condition, the action of participant O n belongs to a given compact set:

[0105] ,

[0106] ,

[0107] where, ,

[0108] ;

[0109] According to the above (1) and (2), the electric vehicle between two adjacent critical points and will find the electric vehicle charging station O n which is the most cost-effective among all the electric vehicle charging stations;

[0110] The demand length (L) of electric vehicle charging station O n is defined as , which is expressed as:

[0111] ,

[0112] Substitute from (1) into the expression of electric vehicle charging station O n , n∈{1,2,.... N} is expressed as:

[0113] ,

[0114] where, the electric vehicles are uniformly distributed throughout the length L;

[0115] The service price of electric vehicle charging station O n is defined as the price relative to other electric vehicle charging stations O -n ​​ The effect for:

[0116] ,

[0117] The above The expression and Substituting the expression into the above formula, it is simplified to:

[0118] ,

[0119] in, ,and ,

[0120] For uniform distribution , , ,

[0121] ;

[0122] also, ,

[0123] ,

[0124] ,

[0125] In addition, electric vehicle charging stations n The necessary energy Expressed as:

[0126] ;

[0127] (4) When the action set satisfies the market sharing condition in (3), the utility of the description There exists a unique pure strategy NE;

[0128] Define participant O n The reaction function is , specific expressions such as:

[0129] ,

[0130] in, ,

[0131] ,

[0132] ,

[0133] Through differential utility Its behavior The obtained,

[0134] Further, the reaction function is solved to find the NE profile, and the utility corresponding to the NE behavior gives the NE utility for each player.

[0135] 106, according to the appropriate pricing model to regulate each electric vehicle to select the corresponding electric vehicle charging station for charging.

[0136] In the above appropriate pricing model is found to be completed, the pricing and profit of a plurality of electric vehicle charging stations are also determined, and each electric vehicle that needs to be charged can be selected according to the appropriate pricing model to select the corresponding electric vehicle charging station for charging.

[0137] The implementation principle of the embodiment of the present application is:

[0138] The real-time information of the electric vehicle is not required in the appropriate pricing model, and only by setting the energy demand and travel cost expectation value of the electric vehicle in advance, the charging plan can be formulated more quickly.

[0139] It is suitable for the developing market situation, if a new charging station service provider wants to establish its electric vehicle charging station in the existing competition, to utilize the growing charging demand in the market, and to utilize the latest information of the existing market condition to estimate the expected profit of the NE condition of the possible position in advance;

[0140] The energy demand and travel cost of the electric vehicle user are considered, and at the same time, the electric vehicle charging stations of many charging service providers can obtain more profits in the charging market.

[0141] In combination with the electric vehicle charging regulation method based on the comprehensive pricing described in the above embodiment, the electric vehicle charging regulation system based on the comprehensive pricing is described below through an embodiment.

[0142] As Figure 2 shown, the embodiment of the present application provides an electric vehicle charging regulation system based on comprehensive pricing, comprising:

[0143] The model construction module 201 is used for constructing a comprehensive pricing model between a plurality of electric vehicle charging stations, and the target constraint condition of the comprehensive pricing model is that the charging cost of the electric vehicle is minimum, and the profit of the service fee collected by the electric vehicle charging station from the electric vehicle in addition to the energy cost is maximum.

[0144] The charging cost analysis module 202 is used for analyzing the components of the charging cost of the electric vehicle.

[0145] The selection criteria module 203 is configured to classify the components according to the cost, and determine the selection criteria of the electric vehicle charging station of the electric vehicle user according to the classification result of the cost classification;

[0146] The game theory analysis module 204 is configured to analyze the interaction between multiple self-interested electric vehicle charging stations in a market sharing environment by using game theory, and obtain the equilibrium condition of pricing and profit of the multiple electric vehicle charging stations.

[0147] The pricing module 205 is configured to find a suitable pricing model of multiple electric vehicle charging stations participating in competition in a market sharing environment based on the Hotelling game mode.

[0148] The charging regulation module 206 is configured to regulate each electric vehicle to select a corresponding electric vehicle charging station for charging according to the suitable pricing model.

[0149] Based on Figure 2 the embodiments shown in the drawings, preferably, some embodiments of the present application are as follows:

[0150] The model construction module 201 is specifically configured to obtain multiple electric vehicle charging stations located at different positions along a road with a length L; model the projection of the electric vehicle on the highway as being uniformly distributed along the length L, and obtain the uniform probability density function of the electric vehicle as Without loss of generality, the main road is along the x-axis of the Cartesian coordinate system; the set of multiple electric vehicle charging stations is , the charging service provider is located at a distance of , so that , the electric vehicle is ; the charging energy demand of the electric vehicle is modeled as a random variable , and the uniform probability density function of the energy demand is obtained as ; all electric vehicle charging stations are connected to the power grid; the target constraint condition is set as the minimum charging cost of the electric vehicle , and the maximum profit of the electric vehicle charging station charging the electric vehicle except for the energy cost, and the comprehensive pricing model between the multiple electric vehicle charging stations is constructed.

[0151] Based on Figure 2 the embodiments shown in the drawings, preferably, some embodiments of the present application are as follows:

[0152] The charging cost analysis module 202 is specifically configured to analyze the energy cost of the electric vehicle as , represents the energy cost component provided by the electric vehicle charging station O n , denotes the cost per unit of energy of the electric vehicle charging station O n the cost per unit of energy produced;

[0153] the analysis of the electric vehicle costs for the service is , denotes the cost per unit of energy of the electric vehicle charging station O n provided as a component of the service cost, denotes the fixed cost per unit of energy of the electric vehicle charging station O n , is a fixed value;

[0154] the analysis of the electric vehicle costs for the user's travel is , denotes the cost of the travel energy consumed by the electric vehicle to reach the electric vehicle charging station O n , denotes the cost per unit distance of the electric vehicle , denotes the distance between the electric vehicle and the electric vehicle charging station O n , is a random variable subject to a uniform distribution;

[0155] the analysis of the electric vehicle costs for the wait is , denotes the effective cost of the wait for the electric vehicle in the queue at the electric vehicle charging station O n , denotes the cost per unit of time of the electric vehicle , denotes the waiting time at the electric vehicle charging station O n , is a random variable subject to an exponential distribution, the expected waiting time at the electric vehicle charging station O n is ;

[0156] the analysis of the electric vehicle effective charging cost at the electric vehicle charging station O n is ;

[0157] where the electric vehicle is located at at a distance of from the electric vehicle charging station O n ;

[0158] electric vehicles exist Choose an electric vehicle charging station i Compare and choose an electric vehicle charging station j For charging, the extra income is:

[0159] .

[0160] based on Figure 2 The embodiments shown, preferably, some embodiments of the present invention are as follows:

[0161] The selection standard module 203 is specifically used to classify energy cost, service cost, travel expense cost and effective charging cost as travel costs; and determine the electric vehicle charging station selection standard for electric vehicle users as the lowest travel cost or the shortest waiting time based on the travel cost and waiting cost.

[0162] based on Figure 2 The embodiments shown, preferably, some embodiments of the present invention are as follows:

[0163] The game theory analysis module 204 is specifically configured to model electric vehicles as self-interested nodes and set the electric vehicle charging station selection criteria to be the lowest travel cost;

[0164] The expected profit of an electric vehicle charging station is expressed as: ,in, Charging station for electric vehicles n The expected profit, Express expectations, Indicates the number of electric vehicles located within a unit distance, Indicates electric vehicle charging station O n The length segment captured is defined as the required length; Indicates electric vehicle charging station O n Charging pile terminal cost;

[0165] Game theory is used to find the equilibrium conditions for pricing and profits of multiple non-cooperative electric vehicle charging stations; considering the competitive relationship between N electric vehicle charging stations in a price war under the same market sharing environment, the expected profit of each electric vehicle charging station is maximized. For the game model considering the non-cooperative game between N electric vehicle charging stations, the existence of the Nash equilibrium NE condition is proved.

[0166] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0167] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts 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, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0168] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0169] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0170] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A method for regulating electric vehicle charging based on integrated pricing, characterized in that, The application relates to a method for constructing a comprehensive pricing model among multiple electric vehicle charging stations, wherein a target constraint condition of the comprehensive pricing model is that a charging cost of an electric vehicle is minimum, and a profit of the electric vehicle charging station charging a service fee other than an energy cost from the electric vehicle is maximum; analyzing components of the charging cost of the electric vehicle; classifying the components according to a cost classification, and determining an electric vehicle charging station selection standard of an electric vehicle user according to a classification result of the cost classification; analyzing interactions among multiple self-interested electric vehicle charging stations in a market sharing environment by using game theory, and obtaining an equilibrium condition of pricing and profit of the multiple electric vehicle charging stations; finding a suitable pricing model of multiple competitive electric vehicle charging stations in the market sharing environment based on a Hotelling game mode; and regulating each electric vehicle to select a corresponding electric vehicle charging station for charging according to the suitable pricing model. The method for analyzing the interactions among the multiple self-interested electric vehicle charging stations in the market sharing environment by using the game theory, and obtaining the equilibrium condition of the pricing and the profit of the multiple electric vehicle charging stations comprises the following steps. The electric vehicle is modeled as a self-interested node, and the electric vehicle charging station selection standard is set as a lowest travel cost. An equilibrium condition of pricing and profit of multiple non-cooperative electric vehicle charging stations is obtained by using the game theory. The existence of a Nash equilibrium NE condition is proved for a game model considering non-cooperative games among N electric vehicle charging stations. The method for constructing the comprehensive pricing model among the multiple electric vehicle charging stations comprises the following steps. Multiple electric vehicle charging stations are obtained at different positions along a road with a length L. The road is along an x-axis of a Cartesian coordinate system. The method for analyzing the components of the charging cost of the electric vehicle comprises the following steps. The expected profit of the electric vehicle charging station is expressed as: , wherein the Charging station for electric vehicles n The expected profit, Expressing expectations, Indicates the number of electric vehicles located within a unit distance. Represents the electric vehicle charging station O n The length of the captured segment is defined as the required length; Indicates electric vehicle charging station O n The terminal cost of the charging pile; Represents the electric vehicle charging station O n the cost component of the services provided; The method for classifying the components according to the cost classification, and determining the electric vehicle charging station selection standard of the electric vehicle user according to a classification result of the cost classification comprises the following steps.

2. The integrated pricing based electric vehicle charging regulation method of claim 1, wherein, The energy cost, the service cost, the travel expense cost and the effective charging cost are classified as a travel cost. According to the travel cost and the waiting cost, the electric vehicle charging station selection standard of the electric vehicle user is determined as a lowest travel cost or a shortest waiting time. The projection of electric vehicles on the highway is modeled as being uniformly distributed along the length L, resulting in an electric vehicle uniform probability density function of ; The application relates to a method for constructing a comprehensive pricing model among multiple electric vehicle charging stations, wherein a target constraint condition of the comprehensive pricing model is that a charging cost of an electric vehicle is minimum, and a profit of the electric vehicle charging station charging a service fee other than an energy cost from the electric vehicle is maximum; analyzing components of the charging cost of the electric vehicle; classifying the components according to a cost classification, and determining an electric vehicle charging station selection standard of an electric vehicle user according to a classification result of the cost classification; analyzing interactions among multiple self-interested electric vehicle charging stations in a market sharing environment by using game theory, and obtaining an equilibrium condition of pricing and profit of the multiple electric vehicle charging stations; finding a suitable pricing model of multiple competitive electric vehicle charging stations in the market sharing environment based on a Hotelling game mode; and regulating each electric vehicle to select a corresponding electric vehicle charging station for charging according to the suitable pricing model. A set of the plurality of electric vehicle charging stations is located at a distance from a charging service provider such that the electric vehicle is ; The electric vehicle charging energy demand is modeled as a random variable , the energy demand uniform probability density function is obtained as ; all the electric vehicle charging stations are connected to the grid; Set the target constraint for the electric vehicle The charging cost is the smallest, and the electric vehicle charging station charges the electric vehicle The profit is maximized by charging service fees in addition to energy costs, and a comprehensive pricing model among multiple electric vehicle charging stations is constructed.

3. The integrated pricing based electric vehicle charging regulation method of claim 2, wherein, The method for analyzing the interactions among the multiple self-interested electric vehicle charging stations in the market sharing environment by using the game theory, and obtaining the equilibrium condition of the pricing and the profit of the multiple electric vehicle charging stations comprises the following steps. analyzing an energy cost of the electric vehicle , wherein represents an energy cost component provided by the electric vehicle charging station O n represents a unit energy cost generated by the electric vehicle charging station O n ​​​ Analysis of the electric vehicle The service cost is , Represents the electric vehicle charging station O n The cost component of the services provided, Represents the electric vehicle charging station O n The fixed cost per unit of energy, is a fixed value; Analysis of the electric vehicle The travel cost of users is , Indicates the electric vehicle Arrive at the electric vehicle charging station O n The driving energy cost consumed is Indicates the electric vehicle The unit distance travel cost, Indicates the electric vehicle With the electric vehicle charging station O n The distance between is a random variable that obeys a uniform distribution; analyzing a waiting cost of the electric vehicle is , wherein represents an effective waiting cost of the electric vehicle waiting in a queue at the electric vehicle charging station O n , wherein represents a unit time waiting cost of the electric vehicle , wherein represents a waiting time of the electric vehicle charging station O n , wherein is a random variable subject to an exponential distribution, and an expected waiting time of the electric vehicle charging station O n is ; analyzing the electric vehicle at the electric vehicle charging station O n effective charging cost of the charging is ; The Wherein, the electric vehicle Located The distance between the electric vehicle charging station O n is ; The electric vehicle At the Selecting an electric vehicle charging station O i Performing charging, compared to selecting an electric vehicle charging station O j Performing charging, the additional revenue is: ； The For the electric vehicle At the electric vehicle charging station O j The effective charging cost of charging, the For the electric vehicle At the electric vehicle charging station O i The effective charging cost of charging.

4. The integrated pricing based electric vehicle charging regulation method of claim 3, wherein, The electric vehicle is modeled as a self-interested node, and the electric vehicle charging station selection standard is set as a lowest travel cost. An equilibrium condition of pricing and profit of multiple non-cooperative electric vehicle charging stations is obtained by using the game theory. The existence of a Nash equilibrium NE condition is proved for a game model considering non-cooperative games among N electric vehicle charging stations.

5. A comprehensive pricing-based electric vehicle charging regulation system, characterized in that, The method for constructing the comprehensive pricing model among the multiple electric vehicle charging stations comprises the following steps. Multiple electric vehicle charging stations are obtained at different positions along a road with a length L. The road is along an x-axis of a Cartesian coordinate system. The method for analyzing the components of the charging cost of the electric vehicle comprises the following steps. The method for classifying the components according to the cost classification, and determining the electric vehicle charging station selection standard of the electric vehicle user according to a classification result of the cost classification comprises the following steps. The energy cost, the service cost, the travel expense cost and the effective charging cost are classified as a travel cost. According to the travel cost and the waiting cost, the electric vehicle charging station selection standard of the electric vehicle user is determined as a lowest travel cost or a shortest waiting time. The application relates to a method for constructing a comprehensive pricing model among multiple electric vehicle charging stations, wherein a target constraint condition of the comprehensive pricing model is that a charging cost of an electric vehicle is minimum, and a profit of the electric vehicle charging station charging a service fee other than an energy cost from the electric vehicle is maximum; analyzing components of the charging cost of the electric vehicle; classifying the components according to a cost classification, and determining an electric vehicle charging station selection standard of an electric vehicle user according to a classification result of the cost classification; analyzing interactions among multiple self-interested electric vehicle charging stations in a market sharing environment by using game theory, and obtaining an equilibrium condition of pricing and profit of the multiple electric vehicle charging stations; finding a suitable pricing model of multiple competitive electric vehicle charging stations in the market sharing environment based on a Hotelling game mode; and regulating each electric vehicle to select a corresponding electric vehicle charging station for charging according to the suitable pricing model. The method for analyzing the interactions among the multiple self-interested electric vehicle charging stations in the market sharing environment by using the game theory, and obtaining the equilibrium condition of the pricing and the profit of the multiple electric vehicle charging stations comprises the following steps. The electric vehicle is modeled as a self-interested node, and the electric vehicle charging station selection standard is set as a lowest travel cost. An equilibrium condition of pricing and profit of multiple non-cooperative electric vehicle charging stations is obtained by using the game theory. The existence of a Nash equilibrium NE condition is proved for a game model considering non-cooperative games among N electric vehicle charging stations. The method for constructing the comprehensive pricing model among the multiple electric vehicle charging stations comprises the following steps. Multiple electric vehicle charging stations are obtained at different positions along a road with a length L. The road is along an x-axis of a Cartesian coordinate system. The method for analyzing the components of the charging cost of the electric vehicle comprises the following steps. The method for classifying the components according to the cost classification, and determining the electric vehicle charging station selection standard of the electric vehicle user according to a classification result of the cost classification comprises the following steps. The energy cost, the service cost, the travel expense cost and the effective charging cost are classified as a travel cost. According to the travel cost and the waiting cost, the electric vehicle charging station selection standard of the electric vehicle user is determined as a lowest travel cost or a shortest waiting time. A game theory analysis module is configured to model the electric vehicle as a self-regarding node and set the electric vehicle charging station selection criterion as the lowest travel cost; and an expression of an expected profit of the electric vehicle charging station is: wherein the is an expected profit of the electric vehicle charging station O n , the represents expectation, the represents the number of electric vehicles positioned per unit distance, the represents a length of a captured length section of the electric vehicle charging station O n , the represents a charging pile terminal cost of the electric vehicle charging station O n , the represents a service cost component provided by the electric vehicle charging station O n ; a game theory is used to obtain an equilibrium condition of pricing and profit of a plurality of non-cooperative electric vehicle charging stations; in consideration of a competitive relationship among N electric vehicle charging stations in a price war under a same market sharing environment, an expected profit of each electric vehicle charging station is maximized; and for a game model considering non-cooperative game among the N electric vehicle charging stations, existence of a Nash equilibrium NE condition is proved. a pricing module configured to find a suitable pricing model of the plurality of electric vehicle charging stations participating in competition in a market sharing environment based on a Hotelling game mode; a charging regulation module configured to regulate each electric vehicle to select a corresponding electric vehicle charging station for charging according to the suitable pricing model. 6.The electric vehicle charging regulation system based on comprehensive pricing according to claim 5, characterized in that, The model construction module is specifically configured to acquire a plurality of electric vehicle charging stations located at different positions along a road with a length L; model the projection of electric vehicles on the highway as being uniformly distributed along the length L, to obtain an electric vehicle uniform probability density function as ; the road is along an x-axis of a Cartesian coordinate system; a set of the plurality of electric vehicle charging stations is , a charging service provider is located at a distance of , such that , an electric vehicle is ; the charging energy demand of the electric vehicle is modeled as a random variable , to obtain an energy demand uniform probability density function as ; all of the electric vehicle charging stations are connected to a power grid; a target constraint condition is set as a minimum charging cost of the electric vehicle , and a maximum profit of the electric vehicle charging station charging the electric vehicle a service fee in addition to an energy cost, to construct a comprehensive pricing model between the plurality of electric vehicle charging stations. 7.The electric vehicle charging regulation system based on comprehensive pricing according to claim 6, characterized in that, The charging cost analysis module is specifically configured to analyze the energy cost of the electric vehicle , wherein the energy cost of the electric vehicle is represented by , the energy cost component provided by the electric vehicle charging station O n , and the unit energy cost generated by the electric vehicle charging station O n is represented by . analyzing the service cost of the electric vehicle is , wherein represents a service cost component provided by the electric vehicle charging station O n , and wherein represents a fixed cost per unit of energy of the electric vehicle charging station O n , and wherein is a fixed value; analyzing trip cost of the user of the electric vehicle is , wherein represents the travel energy cost consumed by the electric vehicle to reach the electric vehicle charging station O n , wherein represents the unit distance trip cost of the electric vehicle , wherein represents the distance between the electric vehicle and the electric vehicle charging station O n , wherein is a random variable subject to uniform distribution; analyzing a waiting cost of the electric vehicle is , wherein represents an effective waiting cost of the electric vehicle waiting in a queue at the electric vehicle charging station O n , wherein represents a unit time waiting cost of the electric vehicle , wherein represents a waiting time of the electric vehicle charging station O n , wherein is a random variable subject to an exponential distribution, and an expected waiting time of the electric vehicle charging station O n is ; analyzing the electric vehicle at the electric vehicle charging station O n effective charging cost of the charging is ; The Wherein, the electric vehicle Located The distance between the electric vehicle charging station O n The distance is ; The electric vehicle At the Selecting an electric vehicle charging station O i Carrying out charging compared to selecting an electric vehicle charging station O j Carrying out charging, the additional revenue is: ； The For the electric vehicle At the electric vehicle charging station O j Effective charging cost of charging, the For the electric vehicle At the electric vehicle charging station O i Effective charging cost of charging. 8.The electric vehicle charging regulation system based on comprehensive pricing according to claim 7, characterized in that, the selection standard module is specifically configured to classify the energy cost, the service cost, the travel cost and the effective charging cost as a travel cost; and determine that the electric vehicle charging station selection standard of the electric vehicle user is a lowest travel cost or a shortest waiting time according to the travel cost and the waiting cost.

Images