Method, device, equipment, medium and product for guiding orderly charging of electric vehicles

Abstract

The present invention discloses an orderly charging guidance method, device, equipment, medium and product for electric vehicles in the field of electric vehicle charging. The method comprises: constructing an objective function for orderly charging guidance that takes into account the charging price of a charging station and the power generation power of a new energy unit for the purpose of maximizing economic benefits; setting constraints for the objective function, the constraints comprising charging price constraints, operating power constraints and distribution network flow constraints; solving the charging price of each charging station for the objective function under the constraints to obtain the optimal charging price of the charging station; regulating the charging station according to the optimal charging price to achieve orderly charging guidance for electric vehicles; the present invention can effectively promote the consumption of new energy while ensuring the effective operation of the distribution network by controlling the charging price of the charging station and guiding the charging load of the electric vehicle in an orderly manner.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging, and in particular to a method, device, equipment, medium and product for guiding orderly charging of electric vehicles. Background Art

[0002] Electric vehicles and renewable energy power generation have developed rapidly in recent years, bringing new opportunities for mankind to solve energy crises and environmental pollution problems. However, the spatial and temporal uncertainty of electric vehicle charging and the uncertainty of wind and solar power output have also brought new challenges to the operation of the power grid. On the one hand, the spatial and temporal distribution of renewable energy such as wind power and solar power has strong volatility and intermittency. With the continuous increase in the penetration rate of renewable energy, it is imperative to smooth out the uncertainty of their output and efficiently absorb such intermittent energy. On the other hand, when electric vehicles are connected to the power grid for charging on a large scale, the power grid will experience "peak on peak", increase system operating costs, and reduce power quality. The disordered charging of large-scale electric vehicle clusters will affect their own charging efficiency and the operating benefits of the distribution network. By guiding the charging load of electric vehicles in an orderly manner, it is possible to effectively promote the consumption of new energy and ensure the effective operation of the distribution network. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method, device, equipment, medium and product for guiding orderly charging of electric vehicles to solve the technical problem that disorderly charging of large-scale electric vehicle clusters causes unsatisfactory charging efficiency and charging benefits.

[0004] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0005] In a first aspect, the present invention provides a method for guiding orderly charging of an electric vehicle, comprising:

[0006] To maximize economic benefits, an objective function for orderly charging guidance is constructed that takes into account the charging price of the charging station and the power generation power of the new energy unit;

[0007] Setting constraints for the objective function, the constraints including charging price constraints, operating power constraints, and distribution network flow constraints;

[0008] Solving the objective function for the charging price of each charging station under the constraint conditions to obtain the optimal charging price of the charging station;

[0009] Charging stations are regulated according to the optimal charging price to achieve orderly charging guidance for electric vehicles.

[0010] Optionally, the objective function is:

[0011] ;

[0012] In the formula, Income from selling electricity to users:

[0013] ;

[0014] For time period Length of time, It is the time period The price of electricity sold to users, For time period user The load power, is the total number of time periods for selling electricity to users, is the total number of users;

[0015] In the formula, Charging an electric car costs:

[0016] ;

[0017] For charging stations In time period Charging price and charging power, is the total number of charging stations;

[0018] In the formula, Expenditure on purchasing electricity from the higher-level power grid:

[0019] ;

[0020] For the time period The price of electricity purchased from the upper-level power grid and the power output to the upper-level power grid;

[0021] In the formula, Operating costs for power generation:

[0022] ;

[0023] ;

[0024] The power generation and operation costs of distributed generators and new energy generators. For distributed generators In time period Power generation The power generation operating cost under is the total number of distributed generating units;

[0025] In the formula, Dispatch costs for electric vehicles:

[0026] ;

[0027] for Charging station in the market In time period The amount of price increases and decreases in electricity sales, For charging stations In time period The amount of active power increase and decrease;

[0028] In the formula, Green certificate transaction cost:

[0029] ;

[0030] ;

[0031] ;

[0032] ;

[0033] ;

[0034] ;

[0035] is the green electricity trading price, The green electricity quota required by the system and the number of green certificates obtained for renewable energy power generation; For the node Time period Active Power The adjustment value of For the node Time period Internal new energy unit The active and reactive power generated, is the total number of new energy units, is the intermediate parameter, The number of green certificates sold by the system, The coefficient for converting renewable energy power generation into green certificates. is the green certificate transaction price ratio, It is the initial transaction price of the green certificate.

[0036] Optionally, the charging station In time period Charging power The acquisition process includes:

[0037] Get time period Estimated arrival time at charging station Number of users and from charging station Transfer to charging station Number of users , calculate the time period User from charging station Transfer to charging station The transition probability :

[0038] ;

[0039] Based on the transition probability Constructing a price impact model:

[0040] ;

[0041] In the formula, is the expected difference in charging price; For charging stations and charging stations In time period The charging price difference;

[0042] Transfer probability based on price impact model Correction is performed to obtain the corrected transition probability :

[0043] ;

[0044] Based on the modified transition probability Number of users Make corrections to get the corrected number of users :

[0045] ;

[0046] Based on the corrected number of users Determine the time period Considering the impact of charging price, charging station Number of users :

[0047] ;

[0048] In the formula, For time period Estimated arrival time at charging station The number of users, For time period Charging Station The original number of users, For time period Charging Station The number of users who left

[0049] Based on the number of users Computing charging stations In time period Charging power :

[0050] ;

[0051] In the formula, For time period Charging Station The expected average load power of the users in Time period Charging Station The expected distribution probability of connected charging piles for users in the network.

[0052] Optionally, the charging price constraint is:

[0053] ;

[0054] ;

[0055] ;

[0056] In the formula, For charging stations In time period The charging price, are the upper and lower limits of charging prices, is the expected charging price, is the expected coefficient, , For charging stations and charging stations In time period The charging price difference, and , is the total number of charging stations.

[0057] Optionally, the operating power constraint includes:

[0058] Power generation constraints of distributed generators:

[0059] ;

[0060] In the formula, The upper and lower limits of the power generation of the distributed generator set;

[0061] Charging power constraints of charging stations:

[0062] ;

[0063] In the formula, For charging stations The upper limit of charging power;

[0064] Constraints on the increase and decrease of active power of charging stations:

[0065] ;

[0066] ;

[0067] ;

[0068] ;

[0069] ;

[0070] In the formula, For time period Considering the impact of charging price, charging station The number of users, For time period Charging Station The expected average load power of the users; is the regulation ratio of the total charging power;

[0071] Transmission power constraints of tie lines:

[0072] ;

[0073] ;

[0074] In the formula, It is the upper limit of active power and reactive power transmitted by the upper-level power grid tie line.

[0075] Optionally, the power flow constraint of the distribution network is:

[0076] ;

[0077] ;

[0078] In the formula, For the node Time period Distributed generator sets The active and reactive power generated, For the node Time period Internal new energy unit Active and reactive power generated; is the total number of distribution network nodes;

[0079] ;

[0080] ;

[0081] In the formula, For the node Time period Active Power and reactive power The adjustment value of For charging stations At the node Time period The active and reactive power consumed,

[0082] For charging stations In time period The amount of active power increase and decrease; For charging stations In time period The reactive power increase and decrease amount;

[0083] ;

[0084] ;

[0085] In the formula, For the time period Slave Node To Node The active power and reactive power of For Node The conductance and susceptance of For Node and nodes The conductance and susceptance between For the time period node and nodes The voltage amplitude on For the time period node and nodes The voltage phase angle on

[0086] ;

[0087] ;

[0088] ;

[0089] ;

[0090] In the formula, For Node The upper and lower limits of the voltage amplitude on For Node The upper and lower limits of the voltage phase angle, For the time period Slave Node To Node The upper and lower limits of active power, For the time period Slave Node To Node The upper and lower limits of reactive power.

[0091] In a second aspect, the present invention provides an orderly charging guidance device for electric vehicles, the device comprising:

[0092] The objective function module is used to construct an objective function for orderly charging guidance that takes into account the charging price of the charging station and the power generation power of the new energy unit in order to maximize economic benefits;

[0093] A constraint condition module, used to set constraint conditions for the objective function, wherein the constraint conditions include charging price constraint, operating power constraint and distribution network flow constraint;

[0094] An optimal solution module, used to solve the objective function for the charging price of each charging station under the constraint conditions to obtain the optimal charging price of the charging station;

[0095] The charging guidance module is used to regulate the charging stations according to the optimal charging price and realize orderly charging guidance of electric vehicles.

[0096] In a third aspect, the present invention provides an electronic device, including a processor and a storage medium;

[0097] The storage medium is used to store instructions;

[0098] The processor is used to operate according to the instructions to execute the steps according to the above method.

[0099] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the above method when executed by a processor.

[0100] In a fifth aspect, the present invention provides a computer program product, comprising a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0101] Compared with the prior art, the present invention has the following beneficial effects:

[0102] The present invention provides an orderly charging guidance method, device, equipment, medium and product for electric vehicles. The method aims to maximize economic benefits, constructs an objective function for orderly charging guidance that takes into account the impact of charging station charging prices, and solves the problem of adjusting the charging station and charging time selected by the user through the charging price. On the one hand, it guides the user to charge and improves the charging efficiency. On the other hand, it effectively promotes the consumption of new energy, promotes the use of green energy, and improves operating income. At the same time, in the process of solving the problem, it comprehensively considers the charging price constraints, operating power constraints, and distribution network flow constraints to ensure the safe and stable operation of the distribution network. Its device, equipment, medium and product can achieve the corresponding technical effects by using the above method. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] Figure 1 It is a flow chart of an orderly charging guidance method for an electric vehicle provided by an embodiment of the present invention;

[0104] Figure 2 A structural diagram of the IEEE 33 node power distribution system provided by an embodiment of the present invention;

[0105] Figure 3 The basic load and new energy unit output diagram provided by the embodiment of the present invention;

[0106] Figure 4 The embodiment of the present invention provides the real-time charging price of each charging station obtained by optimization;

[0107] Figure 5 It is a schematic diagram of charging load after an electric vehicle participates in charging guidance provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0108] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0109] Embodiment 1:

[0110] like Figure 1 As shown, an embodiment of the present invention provides an orderly charging guidance method for an electric vehicle, comprising the following steps:

[0111] Step S1: with the purpose of maximizing economic benefits, construct an objective function for orderly charging guidance that takes into account the charging price of the charging station and the power generation power of the new energy unit.

[0112] Specifically in this embodiment, the objective function is:

[0113] ;

[0114] In the formula, Income from selling electricity to users:

[0115] ;

[0116] For time period Length of time, It is the time period The price of electricity sold to users, For time period user The load power, is the total number of time periods for selling electricity to users, is the total number of users;

[0117] In the formula, Charging an electric car costs:

[0118] ;

[0119] For charging stations In time period Charging price and charging power, is the total number of charging stations;

[0120] In the formula, Expenditure on purchasing electricity from the higher-level power grid:

[0121] ;

[0122] For the time period The price of electricity purchased from the upper-level power grid and the power output to the upper-level power grid;

[0123] In the formula, Operating costs for power generation:

[0124] ;

[0125] ;

[0126] The power generation and operation costs of distributed generators and new energy generators. For distributed generators In time period Power generation The power generation operating cost under is the total number of distributed generating units; In this implementation, the default value is 0;

[0127] In the formula, Dispatch costs for electric vehicles:

[0128] ;

[0129] for Charging station in the market In time period The amount of price increases and decreases in electricity sales, For charging stations In time period The amount of active power increase and decrease;

[0130] In the formula, Green certificate transaction cost:

[0131] ;

[0132] ;

[0133] ;

[0134] ;

[0135] ;

[0136] ;

[0137] is the green electricity trading price, The green electricity quota required by the system and the number of green certificates obtained for renewable energy power generation; For the node Time period Active Power The adjustment value of For the node Time period Internal new energy unit The active and reactive power generated, is the total number of new energy units, is the intermediate parameter, The number of green certificates sold by the system, The coefficient for converting renewable energy power generation into green certificates. is the green certificate transaction price ratio, It is the initial transaction price of the green certificate.

[0138] The user's charging behavior will be affected by the charging price of the charging station, so it is necessary to determine the user's transfer probability and then determine the charging power of the charging station. Specifically in this embodiment, the charging station In time period Charging power The acquisition process includes:

[0139] Get time period Estimated arrival time at charging station Number of users and from charging station Transfer to charging station Number of users , calculate the time period User from charging station Transfer to charging station The transition probability :

[0140] ;

[0141] In this embodiment, the estimated parameters can be derived through historical data or predicted through a big data model, and the acquisition method is set according to actual needs.

[0142] Based on the transition probability Constructing a price impact model:

[0143] ;

[0144] In the formula, is the expected difference in charging price;

[0145] Transfer probability based on price impact model Correction is performed to obtain the corrected transition probability :

[0146] ;

[0147] Based on the modified transition probability Number of users Make corrections to get the corrected number of users :

[0148] ;

[0149] Based on the corrected number of users Determine the time period Considering the impact of charging price, charging station Number of users :

[0150] ;

[0151] In the formula, For time period Estimated arrival time at charging station The number of users, For time period Charging Station The original number of users, For time period Charging Station The number of users who left

[0152] Based on the number of users Computing charging stations In time period Charging power :

[0153] ;

[0154] In the formula, For time period Charging Station The expected average load power of the users in Time period Charging Station The expected distribution probability of connected charging piles for users in the network.

[0155] Step S2: setting constraints for the objective function, wherein the constraints include charging price constraints, operating power constraints, and distribution network flow constraints.

[0156] The charging price constraint is:

[0157] ;

[0158] ;

[0159] ;

[0160] In the formula, For charging stations In time period The charging price, are the upper and lower limits of charging prices, is the expected charging price, is the expected coefficient, , For charging stations and charging stations In time period The charging price difference, and , is the total number of charging stations.

[0161] Optionally, operating power constraints include:

[0162] Power generation constraints of distributed generators:

[0163] ;

[0164] In the formula, The upper and lower limits of the power generation of the distributed generator set;

[0165] Charging power constraints of charging stations:

[0166] ;

[0167] In the formula, For charging stations The upper limit of charging power;

[0168] Constraints on the increase and decrease of active power of charging stations:

[0169] ;

[0170] ;

[0171] ;

[0172] ;

[0173] ;

[0174] In the formula, For time period Considering the impact of charging price, charging station The number of users, For time period Charging Station The expected average load power of the users; is the regulation ratio of the total charging power;

[0175] Transmission power constraints of tie lines:

[0176] ;

[0177] ;

[0178] In the formula, It is the upper limit of active power and reactive power transmitted by the upper-level power grid tie line.

[0179] Optionally, the distribution network flow constraint is:

[0180] ;

[0181] ;

[0182] In the formula, For the node Time period Distributed generator sets The active and reactive power generated, For the node Time period Internal new energy unit Active and reactive power generated; is the total number of distribution network nodes;

[0183] ;

[0184] ;

[0185] In the formula, For the node Time period Active Power and reactive power The adjustment value of For charging stations At the node Time period The active and reactive power consumed,

[0186] For charging stations In time period The amount of active power increase and decrease; For charging stations In time period The reactive power increase and decrease amount;

[0187] ;

[0188] ;

[0189] In the formula, For the time period Slave Node To Node The active power and reactive power of For Node The conductance and susceptance of For Node and nodes The conductance and susceptance between For the time period node and nodes The voltage amplitude on For the time period node and nodes The voltage phase angle on

[0190] ;

[0191] ;

[0192] ;

[0193] ;

[0194] In the formula, For Node The upper and lower limits of the voltage amplitude on For Node The upper and lower limits of the voltage phase angle, For the time period Slave Node To Node The upper and lower limits of active power, For the time period Slave Node To Node The upper and lower limits of reactive power.

[0195] Step S3: Solve the objective function for the charging price of each charging station under the constraint conditions to obtain the optimal charging price of the charging station.

[0196] The solution can be solved by calling yalmip+cplex solver in MATLAB. First, define the variables to be solved, then write the constraints and objective function, and then solve the model. The variable to be solved in this implementation is the charging price of the charging station.

[0197] Step S4: regulating the charging station according to the optimal charging price to achieve orderly charging guidance for electric vehicles.

[0198] In the embodiment of the present invention, the IEEE 33-node power distribution system is used to simulate the power distribution network structure. Figure 2 As shown. The access locations of the two photovoltaic facilities are nodes 11 and 20, and the access locations of the three wind turbines are nodes 14, 22, and 27; the access locations of the four distributed generators DG are 15, 18, 24, and 30, with a maximum output power of 400kW; the access locations of the three EV charging stations are nodes 6, 8, and 23, with powers of 600kW, 800kW, and 1000kW respectively; the basic load of the system and the total output of the new energy units are as follows Figure 3 The simulation results of the embodiment of the present invention are described as follows:

[0199] Depend on Figure 3It can be seen that since new energy units include two types of facilities, wind turbines and photovoltaic units, their output has two peaks at 22:00 to 2:00 the next day and from 11:00 to 14:00 in the afternoon, while the peak electricity consumption of the basic load is mainly concentrated in the evening from 17:00 to 20:00. Therefore, a large amount of new energy power generation is abandoned, resulting in a high transaction cost of green certificates. It is necessary to promote the consumption of new energy power generation by reasonably scheduling the charging time of electric vehicle clusters.

[0200] The method provided by the present invention is used to set corresponding charging prices in different time periods to guide the transfer of electric vehicle charging load. The real-time charging prices of each charging station obtained by optimization are as follows: Figure 4 As shown. Figure 4 As shown in the figure, the upper and lower limits of the charging price are set at 0.7 yuan and 1.6 yuan respectively, and the valley period of the charging price is mainly concentrated between 0:00 and 4:00. The peak period of the charging price is mainly concentrated between 16:00 and 20:00. The reason is that from 0:00 to 4:00 is the period when the wind power output is higher and the basic load is lower. A lower charging price can encourage electric vehicles to charge during this period, thereby promoting wind power consumption; while from 16:00 to 20:00 is the period when the basic load is higher, and a higher charging price can promote part of the charging load to be transferred to other periods, thereby reducing the amount of electricity purchased by the distribution system from the upper power grid and the output of DG, and reducing operating costs. From 11:00 to 14:00, the charging price is also reduced because the photovoltaic output is higher during this period. The charging load of electric vehicles guided by the charging price is shown in the figure. Figure 5 As shown in the figure, the peak charging time for electric vehicles is concentrated between 0:00 and 4:00. Since the wind turbines have a higher output at this time and the charging electricity price is lower, the charging loads of the three charging stations have reached the upper limit of the charging power of their respective charging stations. As time goes by, due to the increase in charging prices, the charging load shows an overall downward trend. When the time approaches 17:00, the charging load shows an upward trend until it reaches the power upper limit of the charging station.

[0201] Embodiment 2:

[0202] An embodiment of the present invention provides an orderly charging guidance device for electric vehicles, the device comprising:

[0203] The objective function module is used to construct an objective function for orderly charging guidance that takes into account the charging price of the charging station and the power generation power of the new energy unit in order to maximize economic benefits;

[0204] The constraint module is used to set constraints for the objective function, including charging price constraints, operating power constraints, and distribution network flow constraints;

[0205] The optimal solution module is used to solve the charging price of each charging station for the objective function under the constraint conditions to obtain the optimal charging price of the charging station;

[0206] The charging guidance module is used to regulate the charging stations according to the optimal charging price and realize orderly charging guidance of electric vehicles.

[0207] Embodiment three:

[0208] Based on the first embodiment, the embodiment of the present invention provides an electronic device, including a processor and a storage medium;

[0209] The storage medium is used to store instructions;

[0210] The processor is used to operate according to the instructions to execute the steps according to the above method.

[0211] Embodiment 4:

[0212] Based on the first embodiment, the embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented.

[0213] Embodiment five:

[0214] Based on the first embodiment, the embodiment of the present invention provides a computer program product, including a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0215] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. 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 disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0216] 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 flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. 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.

[0217] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0218] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0219] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for guiding orderly charging of electric vehicles, characterized in that: include: To maximize economic benefits, an objective function for orderly charging guidance is constructed that takes into account the charging price of charging stations and the power generation power of new energy units. Setting constraints for the objective function, the constraints including charging price constraints, operating power constraints, and distribution network flow constraints; Solving the objective function for the charging price of each charging station under the constraint conditions to obtain the optimal charging price of the charging station; Regulate charging stations according to the optimal charging price to guide electric vehicles to charge in an orderly manner; Wherein, the objective function is: ； In the formula, Income from selling electricity to users: ； For time period Length of time, It is the time period The price of electricity sold to users, For time period user The load power, is the total number of time periods for selling electricity to users, is the total number of users; In the formula, Charging an electric car costs: ； For charging stations In time period Charging price and charging power, is the total number of charging stations; In the formula, Expenditure on purchasing electricity from the higher-level power grid: ； For the time period The price of electricity purchased from the upper-level power grid and the power output to the upper-level power grid; In the formula, Operating costs for power generation: ； ； The power generation and operation costs of distributed generators and new energy generators. For distributed generators In time period Power generation The power generation operating cost under is the total number of distributed generating units; In the formula, Dispatch costs for electric vehicles: ； for Charging station in the market In time period The amount of increase and decrease in electricity prices, For charging stations In time period The amount of active power increase and decrease; In the formula, Green certificate transaction cost: ； ； ； ； ； ； is the green electricity trading price, The green electricity quota required by the system and the number of green certificates obtained for renewable energy power generation; For the node Time period Active Power The adjustment value of For the node Time period Internal new energy unit The active and reactive power generated, is the total number of new energy units, is the intermediate parameter, The number of green certificates sold by the system, The coefficient for converting renewable energy power generation into green certificates. is the green certificate transaction price ratio, It is the initial transaction price of the green certificate.

2. The method for guiding orderly charging of electric vehicles according to claim 1, characterized in that: The charging station In time period Charging power The acquisition process includes: Get time period Estimated arrival time at charging station Number of users and from charging station Transfer to charging station Number of users , calculate the time period User from charging station Transfer to charging station The transition probability : ； Based on the transition probability Constructing a price impact model: ； In the formula, is the expected difference in charging price; For charging stations and charging stations In time period The charging price difference; Transfer probability based on price impact model Correction is performed to obtain the corrected transition probability : ； Based on the modified transition probability Number of users Make corrections to get the corrected number of users : ； Based on the corrected number of users Determine the time period Considering the impact of charging prices Number of users : ； In the formula, For time period Estimated arrival time at charging station The number of users, For time period Charging Station The original number of users, For time period Charging Station The number of users who left Based on the number of users Computing charging stations In time period Charging power : ； In the formula, For time period Charging Station The expected average load power of the users in Time period Charging Station The expected distribution probability of connected charging piles for users in the network.

3. The method for guiding orderly charging of electric vehicles according to claim 1, characterized in that: The charging price constraint is: ； ； ； In the formula, For charging stations In time period The charging price, are the upper and lower limits of charging prices, is the expected charging price, is the expected coefficient, , For charging stations and charging stations In time period The charging price difference, and , is the total number of charging stations.

4. The method for guiding orderly charging of electric vehicles according to claim 1, characterized in that: The operating power constraints include: Power generation constraints of distributed generators: ； In the formula, The upper and lower limits of the power generation of the distributed generator set; Charging power constraints of charging stations: ； In the formula, For charging stations The upper limit of charging power; Constraints on the increase and decrease of active power of charging stations: ； ； ； ； ； In the formula, For time period Considering the impact of charging prices The number of users, For time period Charging Station The expected average load power of the users; is the regulation ratio of the total charging power; Transmission power constraints of tie lines: ； ； In the formula, It is the upper limit of active power and reactive power transmitted by the upper-level power grid tie line.

5. The method for guiding orderly charging of electric vehicles according to claim 1, characterized in that: The power flow constraint of the distribution network is: ； ； In the formula, For the node Time period Distributed generator sets The active and reactive power generated, For the node Time period Internal new energy unit Active and reactive power generated; is the total number of distribution network nodes; ； ； In the formula, For the node Time period Active Power and reactive power The adjustment value of For charging stations At the node Time period The active and reactive power consumed, For charging stations In time period The amount of active power increase and decrease; For charging stations In time period The reactive power increase and decrease amount; ； ； In the formula, For the time period Slave Node To Node The active power and reactive power of For Node The conductance and susceptance of For Node and nodes The conductance and susceptance between For the time period node and nodes The voltage amplitude on For the time period node and nodes The voltage phase angle on ； ； ； ； In the formula, For Node The upper and lower limits of the voltage amplitude on For Node The upper and lower limits of the voltage phase angle, For the time period Slave Node To Node The upper and lower limits of active power, For the time period Slave Node To Node The upper and lower limits of reactive power.

6. An orderly charging guidance device for electric vehicles, characterized in that: The device adopts the steps of the electric vehicle orderly charging guidance method according to any one of claims 1 to 5, including: The objective function module is used to construct an objective function for orderly charging guidance that takes into account the charging price of the charging station and the power generation power of the new energy unit in order to maximize economic benefits; A constraint condition module, used to set constraint conditions for the objective function, wherein the constraint conditions include charging price constraint, operating power constraint and distribution network flow constraint; An optimal solution module, used to solve the objective function for the charging price of each charging station under the constraint conditions to obtain the optimal charging price of the charging station; The charging guidance module is used to regulate the charging stations according to the optimal charging price and realize orderly charging guidance of electric vehicles.

7. An electronic device, characterized in that: including processor and storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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