Electric vehicle time-sharing stepped charging control method and system based on historical load

Abstract

The invention relates to the technical field of electric vehicle charging control, and provides an electric vehicle time-sharing stepped charging control method and system based on a historical load, and the method comprises the steps: obtaining the historical load, time-sharing electricity price and electric vehicle charging load demands of a target power distribution area; calculating a time-sharing reference load based on the historical load; constructing a time-sharing stepped charging control model based on the time-sharing reference load, the time-sharing electricity price and the charging load demand of the electric vehicle; and solving the time-sharing charging control model by taking the minimum total charging cost and the minimum load fluctuation degree as targets to obtain an optimal control scheme, and controlling an electric vehicle charging strategy of a target power distribution area through the optimal control scheme. Compared with the prior art, historical load data are considered, the time-sharing charging control precision degree is improved, and the pressure of the peak period of the power grid is effectively relieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric vehicle charging control, and in particular relates to a method and system for controlling time-sharing step charging of an electric vehicle based on historical load. Background Art

[0002] In recent years, with the increasing global attention to environmental protection and sustainable development, coupled with the advancement of electric vehicle technology and the promotion of national policy support, the number of electric vehicles has increased significantly. The rapid growth of electric vehicles is accompanied by the centralized charging of electric vehicles, which may pose a potential threat to the stability and safety of the distribution network, increase the load pressure on the power grid, and even cause overload risks. The time-of-use electricity price strategy guides electric vehicle users to charge during non-peak hours when electricity prices are lower according to the load of the power grid, thereby ensuring the charging needs of users while reducing the pressure on the power grid during peak hours, achieving a balance between power supply and demand and stable power grid operation.

[0003] At present, the existing technology ignores the differences in regional loads and the micro characteristics of distribution stations in time-sharing electric vehicle charging, and relies too much on a unified time-sharing electricity price strategy, making it difficult to accurately match the actual needs of different regions. Due to the obvious differences in historical loads, power consumption structures, and electric vehicle charging behaviors in various distribution stations, the existing technology cannot effectively solve the problem of local overload caused by uneven regional load distribution. In addition, insufficient consideration of dynamic load changes, distributed energy access, and charging demand characteristics of users in different regions further exacerbates the incompatibility of power grid regulation and reduces the efficiency of power grid operation. Summary of the invention

[0004] In order to overcome the defect of the above-mentioned prior art that the difference in regional loads is ignored and leads to uneven power dispatching, the present invention provides a time-sharing step charging control method and system for electric vehicles based on historical loads.

[0005] In order to achieve the above technical effects, the technical solution of the present invention is as follows:

[0006] A method for controlling time-sharing step charging of an electric vehicle based on historical load comprises the following steps:

[0007] Obtain the historical load, time-of-use electricity price and electric vehicle charging load demand of the target distribution station area; calculate the time-of-use reference load based on the historical load;

[0008] Building a time-sharing step charging control model based on the time-sharing reference load, time-sharing electricity price and electric vehicle charging load demand;

[0009] The time-sharing charging control model is solved with the goal of minimizing the total charging cost and the load fluctuation degree, and an optimal control scheme is obtained. The electric vehicle charging strategy of the target distribution station area is controlled by the optimal control scheme.

[0010] The present invention also proposes a time-sharing step-by-step charging control system for electric vehicles based on historical loads, the system comprising:

[0011] Reference load calculation module: used to obtain the historical load, time-of-use electricity price and electric vehicle charging load demand of the target distribution station area; and calculate the time-of-use reference load based on the historical load;

[0012] Solution solving module: It is equipped with a time-sharing step charging control model, which is used to solve the time-sharing charging control model with the goal of minimizing the total charging cost and the load fluctuation degree, and obtain the optimal control solution. The electric vehicle charging strategy of the target distribution station area is controlled by the optimal control solution.

[0013] The present invention also proposes an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the electric vehicle time-sharing step charging control method based on historical load as described in the present invention is implemented.

[0014] Compared with the prior art, the present invention has the following beneficial effects:

[0015] The present invention constructs a time-sharing step charging control model in combination with the historical load data of the target distribution station area, which can effectively adapt to the load characteristics of power grids in different regions and fully take into account regional differences; secondly, the load brought by electric vehicle charging is balanced with "minimizing the degree of load fluctuation" as the optimization goal, reducing the local load peak and fluctuation risks; the charging strategy is optimized with "minimizing the total charging cost" as the goal, effectively reducing the user's charging cost, and at the same time guiding the user to charge during the off-peak period of the power grid, thereby alleviating the pressure during peak periods. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The figure is a flow chart of a time-sharing step charging control method for electric vehicles based on historical load.

[0017] Figure 2 This is a curve of time-sharing charging costs for electric vehicles in a certain distribution station area.

[0018] Figure 3 This is a load comparison chart before and after the time-step charging control in a distribution station.

[0019] Figure 4 The figure is an architectural diagram of a time-sharing step-by-step charging control system for electric vehicles based on historical load. DETAILED DESCRIPTION

[0020] The accompanying drawings are only used for illustrative purposes and are not to be construed as limiting the present invention;

[0021] It is understandable to those skilled in the art that some well-known descriptions may be omitted in the drawings.

[0022] The technical solution of the present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0023] Example 1

[0024] This embodiment proposes a time-sharing step-by-step charging control method for electric vehicles based on historical loads, such as Figure 1 , which is a flow chart of the electric vehicle time-sharing step charging control method based on historical load in this embodiment.

[0025] The electric vehicle time-sharing step charging control method based on historical load proposed in this embodiment includes the following steps:

[0026] Obtain the historical load, time-of-use electricity price and electric vehicle charging load demand of the target distribution station area; calculate the time-of-use reference load based on the historical load;

[0027] Building a time-sharing step charging control model based on the time-sharing reference load, time-sharing electricity price and electric vehicle charging load demand;

[0028] The time-sharing charging control model is solved with the goal of minimizing the total charging cost and the load fluctuation degree, and an optimal control scheme is obtained. The electric vehicle charging strategy of the target distribution station area is controlled by the optimal control scheme.

[0029] In this embodiment, by combining the historical load data of the target distribution station area, time-of-use electricity prices and electric vehicle charging load demand, a time-of-use step charging control model is constructed, which implements an optimization strategy tailored to local conditions, can effectively adapt to the load characteristics of power grids in different regions, and fully takes into account regional differences; secondly, with "minimizing load fluctuations" as the optimization goal, the charging period is allocated according to the load, the load brought by electric vehicle charging is balanced, the local load peak and fluctuation risks are reduced, and the stability and reliability of power grid operation are improved; the charging strategy is optimized with the goal of "minimizing total charging costs", which effectively reduces the user's charging cost, and at the same time guides users to charge during the off-peak period of the power grid, thereby alleviating peak pressure and achieving coordinated optimization of user economy and power grid operation efficiency.

[0030] In an optional embodiment, the historical load includes load data at each moment in a number of cycle times, and the time-sharing reference load at each moment in the target cycle time is calculated based on the historical load, and the expression is as follows:

[0031]

[0032] Among them, P r,j is the reference load at time j within the target cycle time r, λt is the reference load factor for the tth cycle time; P t,j is the historical load at the jth period in the tth period; k is the number of period times included in the historical load data.

[0033] As an exemplary illustration, the cycle time is 24 hours and the value of k is 7.

[0034] In this embodiment, the historical load includes the load data at each moment in a number of cycles, and based on this, the time-sharing reference load at each moment in the target cycle is calculated, fully considering the load change rules in different time periods, fully reflecting the actual load characteristics of the target distribution station area, and providing scientific data support for the charging regulation strategy. By using load data from multiple cycles, the technical solution can dynamically adapt to the periodicity and fluctuation characteristics of regional loads, avoid the problem of "one size fits all" fixed time-of-use electricity prices, and effectively disperse the charging load, reduce the peak pressure of centralized charging on the power grid, and ensure the safe and stable operation of the power grid. In addition, this design supports load balancing optimization, reduces equipment losses caused by high-load operation, and provides reference data for subsequent multi-objective optimization.

[0035] In an optional embodiment, the time-sharing step charging control model includes total charging cost, load fluctuation degree and constraints; the step of solving the time-sharing charging control model includes: obtaining at least one of the total charging cost or the load fluctuation degree to reach a minimum value under the constraints.

[0036] In this embodiment, the time-sharing step charging control model can achieve an effective balance between user economy and grid stability by incorporating the total charging cost, load fluctuation degree and constraints into the model structure, and solving the problem under the constraints to minimize at least one of the total charging cost or the load fluctuation degree.

[0037] Further optionally, the total charging cost is calculated based on the time-of-use electricity price and the electric vehicle charging load demand, and the calculation formula is as follows:

[0038]

[0039] Among them, f1 is the total charging cost; N is the number of electric vehicles; M is the number of sampling moments within the cycle time; P EVij is the charging power of the i-th electric car at time j; e j is the charging electricity price at time j; x ij represents the charging status of the i-th electric car at time j. ij = 0 means that the i-th electric car is not charging at time j. ij =1 means the i-th electric car is charging at time j;

[0040] The load fluctuation degree is calculated based on the electric vehicle charging load demand and the time-sharing reference load, and its calculation expression is as follows:

[0041]

[0042] Where f2 is the load fluctuation degree; P r,j is the reference load at time j within the target cycle time r; P j is the total load value, which represents the sum of the reference load and charging load at time j; is the average value of the load;.

[0043] As an example, the value of M is 96.

[0044] In this embodiment, the total charging cost is minimized, thereby significantly reducing the user's charging cost; and the distribution of charging load is optimized by minimizing the load fluctuation, thereby reducing the pressure of peak load on the grid operation and improving the stability and safety of the grid operation.

[0045] Furthermore, optionally, a multi-objective normalization optimization process is performed on the total charging cost and the load fluctuation degree, and the expression is as follows:

[0046]

[0047] Among them, e min is the minimum value of charging electricity price; e max The maximum value of the charging electricity price.

[0048] In this embodiment, the time-sharing step charging control model needs to avoid the impact of the multi-objective function due to the dimensional difference, so the multi-objective function needs to be normalized and optimized, and the multi-objective function is converted into a single objective function through normalization. By normalizing and optimizing the multi-objective function, the unfairness or imbalance caused by the dimensional difference of different objective functions is eliminated, so that the model can fairly weigh the importance of each objective during the optimization process. After normalization, the model can unify multiple objectives such as minimizing the total charging cost and minimizing the load fluctuation degree into the same optimization framework, thereby improving the efficiency and accuracy of the solution process. In addition, this method makes the optimization results more reasonable, can achieve a scientific balance between different optimization objectives, ensures that the final strategy meets both the economic needs of users and the stability requirements of power grid operation, and improves the reliability and applicability of the model in practical applications.

[0049] In an optional embodiment, the constraint condition includes at least one of the following: a charging power demand constraint, a charging time constraint, a charging vehicle quantity constraint, and a distribution network load rate constraint.

[0050] Specifically, the expression of the charging power demand constraint is as follows:

[0051] SOC exi ≤SOC endi ≤1

[0052] Among them, SOC exi The expected battery state after charging of the i-th electric vehicle; SOC endi The battery status of the i-th electric vehicle after charging is completed.

[0053] Charging time constraint: The charging time required for a single electric vehicle to meet the charging power demand. The expression is as follows:

[0054]

[0055] Where: SOC sti The battery status before charging the i-th electric vehicle; T endi is the time when the charging of the i-th electric car ends; T sti The time when charging of the i-th electric vehicle starts; P i is the charging power of the i-th electric vehicle; C i is the battery capacity of the i-th electric car.

[0056] In particular, for electric vehicle charging users, the starting charging time node must be consistent with the normal working and rest time of ordinary residents, and the additional charging time constraints are as follows:

[0057]

[0058] Constraint on the number of charging vehicles: The current number of charging vehicles must not be greater than the total number of electric vehicles.

[0059] Distribution network load rate constraint: For the distribution network with time-sharing step charging control, regardless of whether it is in a heavy overload state before the time-sharing step charging control, it is necessary to avoid heavy overload of the distribution network as much as possible during the time-sharing step charging control day. The expression is as follows:

[0060] P j ≤0.8S N η

[0061] Among them, S N is the capacity of the distribution transformer, and η is the power factor of the distribution transformer.

[0062] In this embodiment, the charging power demand constraint is used to ensure that each electric vehicle meets the user's expected battery status requirements after charging is completed, thereby improving the practicality and user acceptance of the strategy. The charging time constraint combines the charging power, battery capacity and charging status to dynamically calculate the required time, and at the same time takes into account the normal work and rest time of ordinary residents to avoid interference of charging behavior on the user's daily life and improve user experience. By limiting the number of charging vehicles, the number of electric vehicles charged at the same time is limited to not exceed the maximum carrying capacity of the charging facility, avoiding equipment damage or reduced efficiency due to overload use, and improving the safety and stability of system operation. The distribution network load rate constraint effectively prevents the distribution network from being overloaded during the implementation of time-sharing step charging control. The charging load distribution is dynamically optimized through constraint conditions to avoid exceeding the capacity and power factor limits of the distribution transformer, and to ensure the reliability of the distribution network operation. This embodiment enhances the adaptability of the time-sharing step charging control model to actual complex scenarios through the setting of multiple constraint conditions, which not only meets the charging needs of individual users, but also optimizes the operating efficiency and safety of the distribution network as a whole, making the model more scientific, accurate and reliable.

[0063] In an optional embodiment, the optimal control scheme includes a time-sharing step-charging arrangement scheme for electric vehicles and a power control scheme for electric vehicle charging piles; the time-sharing step-charging arrangement scheme for electric vehicles controls the charging state of the electric vehicle; the power control scheme for electric vehicle charging piles controls the charging power of the electric vehicle.

[0064] In this embodiment, the optimal control scheme combines the electric vehicle time-sharing step charging arrangement scheme with the charging pile power control scheme to achieve refined management and dynamic optimization of the charging process. The charging time is reasonably allocated through the time-sharing step charging arrangement scheme, and the charging status of the electric vehicle is dynamically controlled, which effectively alleviates the peak load pressure of the power grid and reduces the charging costs of users. The charging power is flexibly adjusted through the charging pile power control scheme to meet the charging needs of users while reducing equipment overload and loss, which significantly improves the charging efficiency, economy and safety of power grid operation.

[0065] As an example, a distribution transformer capacity of a distribution substation is 315kVA, and historical load information and time-of-use electricity price information are collected. There are 10 electric vehicles that accept time-of-use charging control, with an average battery capacity of 100kWh and an average charging power of 7kW. The starting charging battery capacity follows the random distribution of the maximum battery capacity of [0.05, 0.25], and the ending charging battery capacity follows the random distribution of the maximum battery capacity of [0.9, 1]. Figure 2 As shown in Figure 1, it is the time-sharing charging cost curve of electric vehicles in the distribution station area. A certain day is selected as the time-sharing step charging control day for detailed calculation examples. The time-sharing step charging arrangement plan for electric vehicles is obtained as shown in Table 1.

[0066] Table 1: Time-sharing and step-by-step charging arrangement for electric vehicles in a certain area

[0067]

[0068] As can be seen from the table above, since the basic load of this area is a bi-peak load at noon and at night, the time-sharing step charging control scheme is distributed during the load valley period to achieve the best control target. Depending on the different initial battery capacity states of electric vehicles, the required charging time also varies.

[0069] The power control scheme of electric vehicle charging pile is shown in Table 2.

[0070] Table 2 Power control scheme of electric vehicle time-sharing step charging pile in a certain area

[0071]

[0072] It can be seen from Table 1 that if no method is adopted to control the power of time-sharing and step-by-step charging piles for electric vehicles in the substation, the substation will be prone to heavy overload risks during the time periods of 13:00-14:30 in the afternoon and 20:00-23:00 at night. Time-sharing and step-by-step charging pile power control is required to avoid heavy overload of substation equipment, which is the control scheme shown in Table 2.

[0073] like Figure 3 As shown in the figure, it is a load comparison diagram before and after the time-step charging control of the distribution station. Figure 3 It can be seen that after the electric vehicle time-sharing step charging control method based on historical load proposed in this embodiment, the blue line is significantly lower than the red line of random access charging load. It can be seen that the method of the present invention can realize regional electric vehicle time-sharing charging control based on historical load, effectively alleviate power grid load fluctuations, and optimize power resource allocation.

[0074] Example 2

[0075] This embodiment proposes a time-sharing step charging control system for electric vehicles based on historical loads, and applies a time-sharing step charging control method for electric vehicles based on historical loads proposed in Example 1. Figure 4 , which is an architecture diagram of an electric vehicle time-sharing step charging control system based on historical load in this embodiment.

[0076] This embodiment proposes a time-sharing step-by-step charging control system for electric vehicles based on historical loads, including:

[0077] Reference load calculation module: used to obtain the historical load, time-of-use electricity price and electric vehicle charging load demand of the target distribution station area; and calculate the time-of-use reference load based on the historical load;

[0078] Solution solving module: It is equipped with a time-sharing step charging control model, which is used to solve the time-sharing charging control model with the goal of minimizing the total charging cost and the load fluctuation degree, and obtain the optimal control solution. The electric vehicle charging strategy of the target distribution station area is controlled by the optimal control solution.

[0079] It can be understood that the system of this embodiment corresponds to the method of the above-mentioned embodiment 1, and the options in the above-mentioned embodiment 1 are also applicable to this embodiment, so they will not be described repeatedly here.

[0080] Example 3

[0081] This embodiment proposes a computer device, including a memory and a processor, wherein the memory stores computer-readable instructions, wherein when the computer-readable instructions are executed by the processor, the processor executes the steps of a time-sharing step charging control method for electric vehicles based on historical load proposed in Example 1.

[0082] Example 4

[0083] This embodiment proposes a storage medium having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by a processor, implement the steps of a method for controlling time-sharing and step-by-step charging of an electric vehicle based on historical load proposed in Embodiment 1.

[0084] Exemplarily, the storage medium includes, but is not limited to, a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0085] Exemplarily, the instructions, programs, code sets or instruction sets may be implemented using conventional programming languages.

[0086] Exemplarily, the processor includes but is not limited to a smart phone, a personal computer, a server, a network device, etc., and is used to execute all or part of the steps of a time-sharing step charging control method for an electric vehicle based on historical load described in Example 1.

[0087] The terms in the drawings are for illustrative purposes only and should not be construed as limiting this patent;

[0088] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the embodiments here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A time-sharing step charging control method for electric vehicles based on historical load, characterized in that: The following steps are involved: Obtain the historical load, time-of-use electricity price and electric vehicle charging load demand of the target distribution station area; calculate the time-of-use reference load based on the historical load; Building a time-sharing step charging control model based on the time-sharing reference load, time-sharing electricity price and electric vehicle charging load demand; The time-sharing charging control model is solved with the goal of minimizing the total charging cost and the load fluctuation degree, and an optimal control scheme is obtained. The electric vehicle charging strategy of the target distribution station area is controlled by the optimal control scheme.

2. The electric vehicle time-sharing step charging control method based on historical load according to claim 1 is characterized in that: The historical load includes the load data at each moment in a number of cycles; the time-sharing reference load at each moment in the target cycle is calculated based on the historical load, and the expression is as follows: Among them, P r,j is the reference load at time j within the target cycle time r, λ t is the reference load factor for the tth cycle time; P t,j is the historical load at the jth period in the tth period; k is the number of period times included in the historical load data.

3. The electric vehicle time-sharing step charging control method based on historical load according to claim 1 is characterized in that: The time-sharing step charging control model includes total charging cost, load fluctuation degree and constraint conditions; the step of solving the time-sharing charging control model includes: obtaining at least one of the total charging cost or the load fluctuation degree to reach a minimum value under the constraint conditions.

4. The electric vehicle time-sharing step charging control method based on historical load according to claim 3 is characterized in that: The total charging cost is calculated based on the time-of-use electricity price and the electric vehicle charging load demand, and the calculation formula is as follows: Among them, f1 is the total charging cost; N is the number of electric vehicles; M is the number of sampling moments within the cycle time; P EVij is the charging power of the i-th electric car at time j; e j is the charging electricity price at time j; x ij represents the charging status of the i-th electric car at time j. ij = 0 means that the i-th electric car is not charging at time j. ij =1 means the i-th electric car is charging at time j; The load fluctuation degree is calculated based on the electric vehicle charging load demand and the time-sharing reference load, and its calculation expression is as follows: Where f2 is the load fluctuation degree; P r,j is the reference load at time j within the target cycle time r; P j is the total load value, which represents the sum of the reference load and charging load at time j; is the average value of the load.

5. The electric vehicle time-sharing step charging control method based on historical load according to claim 4 is characterized in that: The total charging cost and load fluctuation degree are subjected to multi-objective normalization optimization, and the expression is as follows: Among them, e min is the minimum value of charging electricity price; e max The maximum value of the charging electricity price.

6. The electric vehicle time-sharing step charging control method based on historical load according to claim 3 is characterized in that: The constraint condition includes at least one of the following: a charging power demand constraint, a charging time constraint, a charging vehicle quantity constraint, and a distribution network load rate constraint.

7. The electric vehicle time-sharing step charging control method based on historical load according to any one of claims 1 to 6, characterized in that: The optimal control scheme includes a time-sharing and step-by-step charging arrangement scheme for electric vehicles and a power control scheme for electric vehicle charging piles; the time-sharing and step-by-step charging arrangement scheme for electric vehicles is used to control the charging state of electric vehicles; the power control scheme for electric vehicle charging piles is used to control the charging power of electric vehicles.

8. A time-sharing step charging control system for electric vehicles based on historical load, applying the time-sharing step charging control method for electric vehicles based on historical load according to any one of claims 1 to 7, characterized in that: The system comprises: Reference load calculation module: used to obtain the historical load, time-of-use electricity price and electric vehicle charging load demand of the target distribution station area; and calculate the time-of-use reference load based on the historical load; Solution solving module: It is equipped with a time-sharing step charging control model, which is used to solve the time-sharing charging control model with the goal of minimizing the total charging cost and the load fluctuation degree, and obtain the optimal control solution. The electric vehicle charging strategy of the target distribution station area is controlled by the optimal control solution.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the electric vehicle time-sharing step charging control method based on historical load is implemented as described in any one of claims 1 to 7.

10. A storage medium having computer-readable instructions stored thereon, characterized in that: When the computer-readable instructions are executed by the processor, the electric vehicle time-sharing step-charging control method based on historical load as described in any one of claims 1 to 7 is implemented.

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