Ordered charging method for multi-type charging stations considering optimal operation requirements of power distribution network

Abstract

The application discloses a kind of orderly charging methods of multiple types of charging stations considering the optimization operation demand of distribution network, considering that different types of charging stations are distributed in city, according to the charging characteristics of electric vehicle users, different charging stations undertake different responsibilities and functions to meet the charging needs of different types of electric vehicle users.According to the difference of construction site, charging stations are mainly divided into three categories: private charging stations, public charging stations and fast charging stations.Based on the charging characteristics of electric vehicles, combined with the operation characteristics of various charging stations, an effective charging station orderly charging planning strategy can be proposed, which is a multiple type charging station orderly charging model considering the optimization operation demand of distribution network, to achieve the charging of distribution network load ratio more or less, and to achieve the reasonable use of multiple type charging stations, to balance the network loss to the greatest extent under the condition of ensuring the normal operation of distribution network, to meet the effectiveness and sustainability of electric vehicle charging.

Description

Technical Field

[0001] This invention relates to the field of charging station technology, and in particular to an orderly charging method for multiple types of charging stations that takes into account the needs of optimized operation of power distribution networks. Background Technology

[0002] As the number of electric vehicles continues to increase, charging infrastructure needs to meet the charging demands exceeding the needs of electric vehicles. Meanwhile, due to current limitations in battery capacity and driving range, urban driving is the primary application scenario for electric vehicles. Therefore, rationally planning an orderly charging strategy for various types of charging stations within cities, tailored to the different needs of different electric vehicle users, is both urgent and of significant practical importance.

[0003] Regarding the planning of electric vehicle charging facilities, scholars at home and abroad have conducted relevant research. Reference [1] calculated the spatiotemporal distribution of charging load and used charging distance to measure the impact of charging stations on users; Reference [2] proposed a multi-objective planning method for charging stations based on the random probability behavior characteristics of taxis and the reliability of road travel time; Reference [3] discussed the impact of various charging modes on the optimized operation of charging stations from the perspective of intraday optimal scheduling; Reference [4] analyzed the traffic characteristics of electric vehicles and introduced the methods for considering traffic characteristics in load forecasting, charging facility planning and control strategy research.

[0004] The above literature has proposed planning strategies for electric vehicle charging facilities, but it has not considered the different operating characteristics of different charging stations and has failed to effectively plan charging facilities based on their respective characteristics. In contrast, the method proposed in this invention can balance network losses to the greatest extent while ensuring the normal operation of the distribution network, thus satisfying the effectiveness and sustainability of electric vehicle charging.

[0005] References / books:

[0006] Yu Qing, Li Jinghua, Zhao Qianfu, et al. Optimal layout of urban electric vehicle charging stations based on chaotic quantum particle swarm algorithm with adaptive weight adjustment [J]. Electrical Measurement & Instrumentation, 2017, 54(13):110-114, 119.

[0007] Liu Hong, Li Rong, Ge Shaoyun, et al. Multi-objective programming of charging stations considering the stochastic behavior characteristics of taxis and the reliability of road network travel time [J]. Power System Technology, 2016, 40(2): 433-441.

[0008] Wang Yifeng. Research on the Application of Multi-Objective Optimization Algorithm in Power Systems [D]. Dalian University of Technology, 2019.

[0009] Mei Jie, Gao Ciwei. Considerations of traffic characteristics in the research of electric vehicle grid connection [J]. Power System Technology, 2015, 39(12): 3549-3555. Summary of the Invention

[0010] This invention provides a method for orderly charging of multiple types of charging stations that takes into account the needs of optimized operation of power distribution networks, so as to at least solve the technical problem of unclear planning of electric vehicle charging facilities in related technologies.

[0011] According to one aspect of the present invention, a method for orderly charging of multiple types of charging stations considering the needs of optimized operation of power distribution networks is provided, comprising:

[0012] Determine the charging characteristics of electric vehicles;

[0013] Based on the charging behavior and driving characteristics of electric vehicle users, charging stations are classified according to their charging characteristics.

[0014] Based on the charging characteristics of electric vehicles and the classification results of charging stations, an orderly charging model for multiple types of charging stations is established, taking into account the needs of optimized operation of the power distribution network.

[0015] Solving the ordered charging model of the multi-type charging stations yields the decision results of the ordered charging model of the multi-type charging stations that takes into account the needs of optimized operation of the distribution network. The decision results can ensure that the network loss is balanced to the greatest extent under the normal operation of the distribution network, and meet the effectiveness and sustainability of electric vehicle charging.

[0016] Optionally, the charging characteristics of the electric vehicle include: arrival time, departure time, initial SOC upon arrival, and target SOC upon departure. The mathematical model for the charging characteristics of the electric vehicle is as follows:

[0017]

[0018]

[0019]

[0020]

[0021] In the formula: t arv,i f is the arrival time of the i-th electric vehicle on a weekday; TG μ represents the probability density function of a truncated Gaussian distribution. arv σ is the mean arrival time; arv The standard deviation of arrival time; and These represent the lower and upper limits of the arrival time of the electric vehicle, respectively; N ev For electric vehicles; tdep,i μ represents the departure time of the i-th electric vehicle on a weekday. dep σ represents the average departure time; dep The standard deviation of departure time; and These represent the lower and upper limits of the electric vehicle departure time, respectively; SOC int,i The initial SOC of the i-th electric vehicle on a workday; μ int Let σ be the initial mean SOC of the electric vehicle; int The initial SOC standard deviation; and These represent the lower and upper limits of the initial State of Charge (SOC) value for electric vehicles; SOC tar,i For the target SOC of the i-th electric vehicle; μ tar σ represents the target SOC mean of the electric vehicle; tar The standard deviation of the target SOC; and These represent the lower and upper limits of the target SOC value for electric vehicles, respectively.

[0022] Optionally, charging stations can be classified into three categories based on their charging characteristics:

[0023] Private charging stations are mainly built in residential parking areas and are used to serve primarily private vehicles.

[0024] Public charging stations are mainly built in parking areas of residential areas, workplaces, and commercial areas to serve private vehicles, taxis, and official vehicles.

[0025] Fast charging stations are mainly built along roadsides and can serve private vehicles, taxis, and official vehicles.

[0026] Optionally, the multi-type charging station orderly charging model aims to minimize distribution network losses, considering both electric vehicle constraints and distribution network operation constraints. The objective function of the multi-type charging station orderly charging model is:

[0027]

[0028] In the formula: T is the set consisting of all time periods; S represents the network active power loss of the system during time period t; base This is the system's reference power.

[0029] Optionally, the electric vehicle constraints include electric vehicle charging characteristic constraints and orderly charging constraints for multiple types of charging stations. The electric vehicle charging characteristic constraints are set according to the charging characteristics of the electric vehicle, and the orderly charging constraints for multiple types of charging stations include: electric vehicle charging power constraints, SOC continuity constraints, SOC upper and lower limit constraints, and electric vehicle charging demand constraints.

[0030] Optionally, the distribution network operation constraints include power flow constraints and security constraints.

[0031] Optionally, the decision results include the charging power of different types of electric vehicles at different time periods.

[0032] According to another aspect of the present invention, a multi-type orderly charging device for charging stations that considers the needs of optimized operation of power distribution networks is also provided, comprising:

[0033] A charging characteristic determination module is used to determine the charging characteristics of electric vehicles;

[0034] The charging station classification module is used to classify charging stations according to the charging behavior and driving characteristics of electric vehicle users and the charging characteristics of the charging stations.

[0035] The multi-type charging station orderly charging model construction module is used to combine the charging characteristics of the electric vehicles and the classification results of the charging stations to establish a multi-type charging station orderly charging model that takes into account the needs of power distribution network optimization operation.

[0036] The decision module is used to solve the orderly charging model of the multi-type charging stations to obtain the decision results of the orderly charging model of the multi-type charging stations considering the needs of power distribution network optimization. The decision results can ensure that the network loss is balanced to the greatest extent under the normal operation of the power distribution network, and meet the effectiveness and sustainability of electric vehicle charging.

[0037] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to execute the orderly charging method for multiple types of charging stations that takes into account the needs of optimized operation of the distribution network as described above.

[0038] According to another aspect of the present invention, a processor is also provided, the processor being configured to run a program, wherein the program, when running, executes the multi-type charging method for charging stations that considers the optimization operation requirements of the distribution network as described above.

[0039] Compared with existing technologies, the present invention has the following advantages:

[0040] In this embodiment of the invention, different types of charging stations are distributed throughout the city. Based on the charging characteristics of electric vehicle users, different charging stations undertake different functions to meet the charging needs of different types of electric vehicle users. According to their construction locations, charging stations are mainly divided into three categories: private charging stations, public charging stations, and fast charging stations. Based on the charging characteristics of electric vehicles and the operational characteristics of various types of charging stations, an effective orderly charging planning strategy for multiple types of charging stations can be proposed. This model considers the optimized operation requirements of the power distribution network, enabling less charging when the power distribution network load is high and more charging when the load is low. This achieves the rational use of multiple types of charging stations, maximizing the balance of network losses while ensuring the normal operation of the power distribution network, and meeting the requirements for the effectiveness and sustainability of electric vehicle charging. Attached Figure Description

[0041] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only one embodiment of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart of an orderly charging method for multiple types of charging stations that takes into account the needs of optimized operation of the power distribution network, according to an embodiment of the present invention. Detailed Implementation

[0043] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0044] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0045] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, apparatus, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0046] Example 1

[0047] According to an embodiment of the present invention, an embodiment of an orderly charging method for multiple types of charging stations considering the needs of optimized operation of distribution networks is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0048] This invention aims to propose an orderly charging strategy for multiple types of charging stations that considers the needs of optimized power distribution network operation. By generating strategies tailored to the charging characteristics of electric vehicles, an orderly charging strategy for multiple types of charging stations is proposed. For example... Figure 1 This is a flowchart of an orderly charging method for multiple types of charging stations that considers the needs of optimized operation of the power distribution network, according to an embodiment of the present invention. Figure 1 As shown, the method includes the following steps:

[0049] Step S1: Determine the charging characteristics of the electric vehicle;

[0050] Step S2: Based on the charging behavior and driving characteristics of electric vehicle users, classify charging stations according to their charging characteristics;

[0051] Step S3: Combining the charging characteristics of the electric vehicles and the classification results of the charging stations, establish an orderly charging model for multiple types of charging stations that takes into account the needs of power distribution network optimization.

[0052] Step S4: Solve the ordered charging model of the multi-type charging station to obtain the decision result of the ordered charging model of the multi-type charging station considering the needs of power distribution network optimization. The decision result can ensure that the network loss is balanced to the greatest extent under the normal operation of the power distribution network, and meet the effectiveness and sustainability of electric vehicle charging.

[0053] The above-mentioned orderly charging method for multiple types of charging stations, which takes into account the needs of optimized operation of the power distribution network, enables the rational use of multiple types of charging stations.

[0054] As an optional embodiment, electric vehicles, as a mobile energy storage resource, can participate in demand response through orderly charging and other means. Therefore, in step S1, the charging characteristics of the electric vehicle include: arrival time, departure time, initial State of Charge (SOC) upon arrival, and target SOC upon departure. These charging characteristics can serve as input to an orderly charging model for multiple types of charging stations. The mathematical model for the charging characteristics of the electric vehicle is as follows:

[0055]

[0056]

[0057]

[0058]

[0059] In the formula: t arv,i f is the arrival time of the i-th electric vehicle on a weekday; TG μ represents the probability density function of a truncated Gaussian distribution. arv σ is the mean arrival time; arv The standard deviation of arrival time; and These represent the lower and upper limits of the arrival time of the electric vehicle, respectively; N ev For electric vehicles; t dep,i μ represents the departure time of the i-th electric vehicle on a weekday. dep σ represents the average departure time; dep Standard deviation of departure time; and These represent the lower and upper limits of the electric vehicle departure time, respectively; SOC int,i The initial SOC of the i-th electric vehicle on a workday; μ int Let σ be the initial mean SOC of the electric vehicle; int The initial SOC standard deviation; and These represent the lower and upper limits of the initial State of Charge (SOC) value for electric vehicles; SOC tar,i For the target SOC of the i-th electric vehicle; μ tar σ represents the target SOC mean of the electric vehicle; tar The standard deviation of the target SOC; and These represent the lower and upper limits of the target SOC value for electric vehicles, respectively.

[0060] Equation (1) represents the probability distribution of the time when the electric vehicle starts charging; Equation (2) represents the probability distribution of the time when the electric vehicle ends charging; Equation (3) represents the initial SOC when the electric vehicle arrives; Equation (4) represents the target SOC when the electric vehicle leaves.

[0061] As an optional implementation, different types of charging stations are distributed throughout the city. Based on the charging behavior and driving characteristics of electric vehicle users, different charging stations perform different functions to meet the charging needs of different types of electric vehicle users. Therefore, step S2 categorizes charging stations into three types according to their construction locations:

[0062] Private charging stations are mainly built in residential parking areas and are used to serve primarily private vehicles.

[0063] Public charging stations are mainly built in parking areas of residential areas, workplaces, and commercial areas to serve private vehicles, taxis, and official vehicles.

[0064] Fast charging stations are mainly built along roadsides and can serve private vehicles, taxis, and official vehicles.

[0065] As an optional embodiment, due to the different driving behaviors and charging modes of electric vehicles, different types of charging stations need to meet different types of charging demands. This is reflected by different values ​​for the mean arrival time, standard deviation of arrival time, mean departure time, standard deviation of departure time, mean initial SOC, standard deviation of initial SOC, mean target SOC, and standard deviation of target SOC. Therefore, in step S3, the ordered charging model for multiple types of charging stations aims to minimize the distribution network loss, considering both electric vehicle constraints and distribution network operation constraints. The objective function of the ordered charging model for multiple types of charging stations is:

[0066]

[0067] In the formula: T is the set consisting of all time periods; S represents the network active power loss of the system during time period t; base This is the system's reference power.

[0068] The goal is to minimize distribution network losses, thereby balancing network losses to the greatest extent possible while ensuring the normal operation of the distribution network, and meeting the requirements for the effectiveness and sustainability of electric vehicle charging.

[0069] As an optional embodiment, the electric vehicle constraints include charging characteristic constraints of electric vehicles and ordered charging constraints of multiple types of charging stations.

[0070] As an optional embodiment, the charging characteristic constraints of electric vehicles are set according to the charging characteristics of electric vehicles, which mainly include the arrival time, departure time, initial SOC upon arrival, and target SOC upon departure, which serve as the data input for the electric vehicle demand response model of the charging station, as shown in equations (1)-(4).

[0071] The pre-set parameters for orderly charging at various types of charging stations include: electric vehicle charging power constraints, State of Charge (SOC) continuity constraints, SOC upper and lower limit constraints, and electric vehicle charging demand constraints. Specifically:

[0072] 1) The charging power constraint for electric vehicles is that the charging power cannot exceed the rated power of the EV battery, expressed as:

[0073] 0≤P c,i,t ≤P rate,i ,t∈T,i∈N ev (6)

[0074] In the formula: P rate,i,t Let P be the rated power of the i-th electric vehicle during time period t. c,i,t Let be the charging power of the i-th electric vehicle during time period t...

[0075] Equation (6) represents the rated power limit for charging electric vehicles.

[0076] 2) The SOC continuity constraint is the variation of the SOC of each EV's onboard battery with charging power, expressed as:

[0077] SOC t,i =SOC t-1,i +η ch ·P c,t-1,i ·Δt / E rate,i ,t∈T,i∈N ev

[0078] Where: SOC t,i Let η be the SOC of the i-th electric vehicle at time t. ch For the charging efficiency of electric vehicles, E rate,i Let P be the rated capacity of the i-th electric vehicle. c,t-1,i N represents the charging power of the i-th electric vehicle during time period t-1; ev A collection of electric vehicles.

[0079] Equation (7) represents the SOC constraint that electric vehicles must meet.

[0080] 3) The upper and lower limits of SOC are constrained so that the SOC of the vehicle battery of each EV must be within a certain range, as shown in Equation (8).

[0081] SOC min,i ≤SOC t,i≤SOC max,i ,t∈T,i∈N ev (8)

[0082] Where: SOC min,i With SOC max,i Let be the lower limit and upper limit of the SOC of the i-th electric vehicle at time t, respectively.

[0083] Equation (8) represents the upper and lower limits of the SOC of electric vehicles.

[0084] 4) Electric vehicle charging demand constraints mean that electric vehicles at charging stations must meet certain charging demands to complete charging. Each electric vehicle starts charging from its initial SOC and must be charged until it reaches its target charging capacity.

[0085]

[0086]

[0087] In the formula: Let t be the arrival time of the i-th electric vehicle. arv,i SOC; SOC int,i Let be the initial SOC of the i-th electric vehicle; For the i-th electric vehicle at time t... dep,i Actual SOC; SOC exp,i Let SOC be the target SOC of the i-th electric vehicle.

[0088] Equations (9)-(10) represent the charging demand constraints of electric vehicles.

[0089] As an optional embodiment, the distribution network operation constraints include power flow constraints and security constraints.

[0090] Specifically:

[0091] 1) Current constraints:

[0092]

[0093]

[0094]

[0095]

[0096] Where: φ E For the set of distribution network branches; N E Let T be the set of distribution network nodes; T is the set consisting of all time periods. These represent the complex power transmitted from node j to node k and from node i to node j in the distribution network during the t-th time period, respectively. The net power injected into node j in the t-th time period; The net power injected into node i in the t-th time period; Z represents the power of the load connected to node j; ij Let be the impedance of line ij; This represents the square of the current amplitude transmitted from node i to node j during the t-th time period; These are the squares of the voltage amplitudes at nodes j and k in the t-th time period, respectively. This represents the square of the current amplitude transmitted from node j to node k during the t-th time period; The variable is 0-1, representing the line recovery status. If the line is restored, the value is "1", otherwise it is "0"; M is a sufficiently large constant.

[0097] Equations (11) to (14) represent the power flow constraints of the distribution network.

[0098] 2) Safety operation constraints:

[0099]

[0100]

[0101] In the formula: These are the squares of the voltage amplitudes at nodes j and k in the t-th time period, respectively. I represents the current amplitude transmitted from node i to node j during the t-th time period. ij,min I ij,max Let be the minimum and maximum values ​​of the current amplitude transmitted from node i to node j during the t-th time period.

[0102] Equations (15) and (16) represent the system safety operation constraints to prevent voltage and current amplitudes from exceeding limits.

[0103] Therefore, the orderly charging model for multiple types of charging stations, considering the needs of optimized operation of the distribution network, is established as follows:

[0104] 1) Objective function: Equation (5).

[0105] 2) Constraints: Equations (1)-(4), Equations (6)-(16).

[0106] As an optional implementation, the orderly charging model of multiple types of charging stations considering the needs of distribution network optimization is solved using the Yalmip optimization modeling toolkit and Gurobi solver in the Matlab language.

[0107] After solving the model, the result is the decision result of the orderly charging model of multiple types of charging stations that takes into account the needs of optimized operation of the distribution network, including the charging power of different types of electric vehicles in different time periods.

[0108] Example 2

[0109] According to another aspect of the present invention, a multi-type charging station orderly charging device considering the needs of distribution network optimization operation is also provided. This device applies the above-described multi-type charging station orderly charging method considering the needs of distribution network optimization operation. The device includes:

[0110] A charging characteristic determination module is used to determine the charging characteristics of electric vehicles;

[0111] The charging station classification module is used to classify charging stations according to the charging behavior and driving characteristics of electric vehicle users and the charging characteristics of the charging stations.

[0112] The multi-type charging station orderly charging model construction module is used to combine the charging characteristics of the electric vehicles and the classification results of the charging stations to establish a multi-type charging station orderly charging model that takes into account the needs of power distribution network optimization operation.

[0113] The decision module is used to solve the orderly charging model of the multi-type charging stations to obtain the decision results of the orderly charging model of the multi-type charging stations considering the needs of power distribution network optimization. The decision results can ensure that the network loss is balanced to the greatest extent under the normal operation of the power distribution network, and meet the effectiveness and sustainability of electric vehicle charging.

[0114] This invention is not limited to the specific embodiments described above. The above are merely preferred embodiments of this invention and are not intended to limit the invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

[0115] Example 3

[0116] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored program, wherein, when the program is executed, the device where the computer-readable storage medium is located executes any of the above-described methods for orderly charging of multiple types of charging stations that consider the needs of optimized operation of the power distribution network.

[0117] Optionally, in this embodiment, the computer-readable storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals, and the computer-readable storage medium includes a stored program.

[0118] Optionally, during program execution, the device containing the computer-readable storage medium may perform the following functions: determine the charging characteristics of electric vehicles; classify charging stations according to their charging characteristics based on the charging behavior and driving characteristics of electric vehicle users; establish a multi-type orderly charging model for charging stations that considers the needs of optimized operation of the distribution network, combining the charging characteristics of the electric vehicles and the classification results of the charging stations; solve the multi-type orderly charging model for charging stations to obtain the decision results of the multi-type orderly charging model that considers the needs of optimized operation of the distribution network, wherein the decision results can ensure that the network loss is balanced to the greatest extent under the normal operation of the distribution network, and meet the requirements of effectiveness and sustainability of electric vehicle charging.

[0119] Example 4

[0120] According to another aspect of the present invention, a processor is also provided for running a program, wherein the program executes any of the above-described methods for orderly charging of multiple types of charging stations that takes into account the requirements for optimized operation of the power distribution network.

[0121] This invention provides a device that includes a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps of an orderly charging method for multiple types of charging stations that takes into account the needs of optimized operation of the power distribution network.

[0122] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0123] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0124] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interface, and the indirect coupling or communication connection of units or modules may be electrical or other forms.

[0125] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0126] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0127] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0128] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for orderly charging of multiple types of charging stations considering the needs of optimized operation of power distribution networks, characterized in that, include: Determine the charging characteristics of electric vehicles; Based on the charging behavior and driving characteristics of electric vehicle users, charging stations are classified according to their charging characteristics. Based on the charging characteristics of electric vehicles and the classification results of charging stations, an orderly charging model for multiple types of charging stations is established, taking into account the needs of optimized operation of the power distribution network. Solving the ordered charging model of the multi-type charging station yields the decision results of the ordered charging model of the multi-type charging station considering the needs of power distribution network optimization. The decision results can ensure the maximum balance of network losses under the normal operation of the power distribution network, and meet the effectiveness and sustainability of electric vehicle charging. The charging characteristics of the electric vehicle include: arrival time, departure time, initial SOC upon arrival, and target SOC upon departure. The mathematical model for the charging characteristics of the electric vehicle is as follows: (1) (2) (3) (4) In the formula: For the first weekday The arrival time of the electric vehicle; This represents the probability density function of a truncated Gaussian distribution; This represents the average arrival time. The standard deviation of arrival time; and These represent the lower and upper limits for the arrival time of electric vehicles, respectively. A collection of electric vehicles; For the first weekday The departure time of the electric vehicle; This represents the average departure time. Standard deviation of departure time; and These represent the lower and upper limits for the electric vehicle departure time, respectively. For the first weekday The initial state of charge (SOC) of an electric vehicle; The initial average SOC of the electric vehicle; The initial SOC standard deviation; and These represent the lower and upper limits of the initial SOC value for electric vehicles, respectively. For the first The target SOC of an electric vehicle; The target SOC average for electric vehicles; The standard deviation of the target SOC; and These represent the lower and upper limits of the target SOC value for electric vehicles, respectively. Based on their charging characteristics, charging stations are divided into three categories: Private charging stations are mainly built in residential parking areas and are used to serve primarily private vehicles. Public charging stations are mainly built in parking areas of residential areas, workplaces, and commercial areas to serve private vehicles, taxis, and official vehicles. Fast charging stations are mainly built along roadsides and can serve private vehicles, taxis, and official vehicles. The multi-type charging station orderly charging model aims to minimize distribution network losses, considering both electric vehicle constraints and distribution network operation constraints. The objective function of the multi-type charging station orderly charging model is: (5) In the formula: T It is a set consisting of all time periods; The network active power loss of the system during time period t; This is the system's reference power.

2. The method for orderly charging of multiple types of charging stations considering the optimized operation requirements of the distribution network as described in claim 1, characterized in that, The electric vehicle constraints include electric vehicle charging characteristic constraints and orderly charging constraints for multiple types of charging stations. The electric vehicle charging characteristic constraints are set according to the charging characteristics of electric vehicles. The orderly charging constraints for multiple types of charging stations include: electric vehicle charging power constraints, SOC continuity constraints, SOC upper and lower limit constraints, and electric vehicle charging demand constraints.

3. The orderly charging method for multiple types of charging stations considering the optimized operation requirements of the distribution network as described in claim 1, characterized in that, The power distribution network operation constraints include power flow constraints and security constraints.

4. The method for orderly charging of multiple types of charging stations considering the optimized operation requirements of the distribution network as described in claim 1, characterized in that, The decision results include the charging power of different types of electric vehicles at different times.

5. A multi-type orderly charging device for charging stations that considers the needs of optimized operation of power distribution networks, characterized in that, The method described in any one of claims 1-4 includes: A charging characteristic determination module is used to determine the charging characteristics of electric vehicles; The charging station classification module is used to classify charging stations according to the charging behavior and driving characteristics of electric vehicle users and the charging characteristics of the charging stations. The multi-type charging station orderly charging model construction module is used to combine the charging characteristics of the electric vehicles and the classification results of the charging stations to establish a multi-type charging station orderly charging model that takes into account the needs of power distribution network optimization operation. The decision module is used to solve the orderly charging model of the multi-type charging stations to obtain the decision results of the orderly charging model of the multi-type charging stations considering the needs of power distribution network optimization. The decision results can ensure that the network loss is balanced to the greatest extent under the normal operation of the power distribution network, and meet the effectiveness and sustainability of electric vehicle charging.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device containing the computer-readable storage medium to perform the orderly charging method for multiple types of charging stations that takes into account the needs of optimized operation of the power distribution network as described in any one of claims 1 to 4.

7. A processor, characterized in that, The processor is used to run a program, wherein the program executes the orderly charging method for multiple types of charging stations that takes into account the needs of optimized operation of the distribution network as described in any one of claims 1 to 4.

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