A method, apparatus, and storage medium for implementing VSG group control in a V2G system.

Abstract

A method, device and storage medium for implementing VSG group control in a V2G system, which relates to the field of VSG group control technology, uses an optimization algorithm to determine the power allocation scheme of each electric vehicle to meet the needs of the power grid, and achieves load balance between electric vehicles through group control strategies to optimize the dispatch of the power system. Enhance system flexibility: Support different types of electric vehicles to participate in grid regulation, and improve system flexibility and responsiveness.

Description

Technical Field

[0001] The present invention relates to the technical field of VSG group control, and in particular to a method, device and storage medium for implementing VSG group control in a V2G system. Background Art

[0002] With the popularity of electric vehicles (EVs), V2G technology, as an emerging power system solution, can use the battery energy storage of electric vehicles for grid regulation. Virtual synchronous generator (VSG), as a control strategy that simulates the characteristics of traditional synchronous generators, helps to improve the stability and power quality of power systems. However, existing VSG technology faces some challenges in V2G systems, such as the coordinated control of multiple electric vehicles, the dynamic response capability of the system, and the real-time regulation of grid loads. Summary of the invention

[0003] In order to overcome the deficiencies of the above technologies, the present invention provides a method, device and storage medium for implementing VSG group control in a V2G system by improving the stability and efficiency of the system through a group control strategy.

[0004] The technical solution adopted by the present invention to overcome the technical problems is:

[0005] A method for implementing VSG group control in a V2G system, comprising:

[0006] S1. Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles ;

[0007] S2. By solving the objective function minimization, we can get Electric vehicles Power distribution at each moment ;

[0008] S3. According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Construct constraints;

[0009] S4. According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time ;

[0010] S5. According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time ;

[0011] S6. Passing speed Get the first Electric vehicles Update location at the moment ;

[0012] S7. The VSG control module of the electric vehicle will update the position As the issued Control instructions for electric vehicles.

[0013] Furthermore, the objective function in step S2 The solution formula for minimizing is as follows:

[0014] In the formula, is the number of time steps in the optimization cycle, for The load deviation weight at the moment, for The weight of unmet demand at the moment, is the total number of electric vehicles, For the The charging and discharging requirements of electric vehicles, is the penalty weight, For the penalty item,

[0015] ,in is the maximum limit of power, The minimum limit for power.

[0016] Further, in step S3, according to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Methods for constructing constraints include:

[0017] S31. By formula Build The permissible range of power distribution for electric vehicles, For the The minimum supported power of an electric vehicle, For the The maximum supported power of an electric vehicle;

[0018] S32. By formula Constructing grid load balancing constraints;

[0019] S33. Through the formula Construct the battery state constraint, where For the Electric vehicles Battery status at all times, is the time step, is the battery capacity, , For the The minimum supported SOC of an electric vehicle, For the The maximum supported SOC of an electric vehicle.

[0020] Further, in step S4, Electric vehicles Power distribution at each moment Bring it into the particle swarm optimization algorithm and randomly generate Electric vehicles The speed of time .

[0021] Further, in step S4, the formula Solve the objective function of minimum power allocation, where For the Electric vehicles Power distribution at all times.

[0022] Further, in step S5, the formula

[0023] Calculate the first Electric vehicles The speed of time , where is the inertia weight, is the individual learning factor, is the social learning factor, , are all random numbers, For the Electric vehicles in The location at the moment, is the global best position.

[0024] Preferably, The value is between 0 and 1. The value is 2. The value is 2. , The value is between 0 and 1.

[0025] Further, in step S6, the formula Calculate the obtained Electric vehicles Update location at the moment .

[0026] On the other hand, the present invention also relates to a device for implementing VSG group control in a V2G system, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; wherein:

[0027] The memory is used to store computer programs;

[0028] The processor is configured to execute, by running a program stored in the memory:

[0029] Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles ;

[0030] By minimizing the objective function, we can obtain Electric vehicles Power distribution at each moment ;

[0031] According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Construct constraints;

[0032] According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time ;

[0033] According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time ;

[0034] Passing speed Get the first Electric vehicles Update location at the moment .

[0035] On the other hand, the present invention also relates to a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements:

[0036] Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles ;

[0037] By minimizing the objective function, we can obtain Electric vehicles Power distribution at each moment ;

[0038] According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Construct constraints;

[0039] According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time ;

[0040] According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time ;

[0041] Passing speed Get the first Electric vehicles Update location at the moment .

[0042] The beneficial effects of the present invention are: using an optimization algorithm to determine the power allocation scheme of each electric vehicle to meet the needs of the power grid, achieving load balance between electric vehicles through group control strategies, and optimizing the dispatch of the power system. Enhance system flexibility: support different types of electric vehicles to participate in power grid regulation, and improve the flexibility and responsiveness of the system. DETAILED DESCRIPTION

[0043] The present invention is further described below so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0044] In the description of the present invention, it should be noted that the embodiments described in the present invention are only part of the embodiments of the present invention, rather than all of the embodiments; based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0045] The terms "first", "second", etc. in the specification and claims of this article are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of this article described here can be implemented in an order other than those described. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0046] Example 1

[0047] A method for implementing VSG group control in a V2G system, comprising:

[0048] S1. Collection Electric vehicles Battery status at the moment (SOC, State of Charge) , Expected grid load at time (Unit: W), Charging and discharging requirements of electric vehicles .

[0049] S2. By solving the objective function minimization, we can get Electric vehicles Power distribution at each moment (Unit: W), the goal is to find the power distribution of each electric vehicle Minimize the objective function.

[0050] S3. According to Electric vehicles Power distribution at the moment (charging or discharging) , No. Electric vehicles Battery status at all times Build constraints.

[0051] S4. According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time .

[0052] S5. According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time .

[0053] S6. Passing speed Get the first Electric vehicles Update location at the moment .

[0054] S7. The VSG control module of the electric vehicle will update the position As the issued Control instructions for electric vehicles.

[0055] The central controller calculates the global optimal power allocation scheme to balance the grid load and meet the charging and discharging requirements of each electric vehicle. The solution formula for minimizing (representing the total cost of optimization, unit: dimensionless) is as follows:

[0056] In the formula, is the number of time steps in the optimization cycle (unit: dimensionless), for The load deviation weight at the moment (unit: dimensionless), for The weight of unmet demand at the moment (unit: dimensionless), is the total number of electric vehicles (unit: dimensionless), For the The charging and discharging requirements of electric vehicles (unit: W), which can include the charging or discharging amount, is the penalty weight, which is used to control the impact of the penalty term on the objective function (unit: dimensionless), For the penalty item,

[0057] ,in is the maximum limit of power, The minimum limit for power.

[0058] In this embodiment, in step S3, according to Electric vehicles Power distribution at each moment (Charging is positive, discharging is negative), Electric vehicles Battery status at all times Methods for constructing constraints include:

[0059] S31. By formula Build The permissible range of power distribution for electric vehicles, For the The minimum supported power of an electric vehicle, For the The maximum supported power of an electric vehicle.

[0060] S32. By formula Construct grid load balancing constraints.

[0061] S33. Through the formula Construct the battery state constraint, where For the Electric vehicles Battery status at all times, is the time step (in seconds), is the battery capacity (unit: Wh), , For the The minimum supported SOC of an electric vehicle, For the The maximum supported SOC of an electric vehicle.

[0062] In this embodiment, in step S4, Electric vehicles Power distribution at each moment Bring it into the particle swarm optimization algorithm and randomly generate Electric vehicles The speed of time , with the goal of minimizing power distribution changes and maximizing Chengdu to protect electric vehicle batteries.

[0063] In this embodiment, in step S4, the formula Solve the objective function of minimum power allocation, where For the Electric vehicles Power distribution at all times.

[0064] In this embodiment, in step S5, the formula

[0065] Calculate the first Electric vehicles The speed of time , where is the inertia weight, which controls the degree to which the particle is retained in the current search direction. is the individual learning factor, which affects the degree to which the particle moves to its optimal position. is the social learning factor, which affects the degree to which particles move to the global optimal position. , are all random numbers, used to introduce randomness and make the search more diverse. For the Electric vehicles in The position at the time (optimal power allocation to), is the global optimal position (the optimal power allocation value found among all particles). Particle swarm optimization (PSO) searches for the optimal solution by adjusting the speed and position of particles. In the power allocation problem, defining the fitness function and selecting parameters reasonably can effectively optimize the power allocation scheme. Through continuous iteration, PSO can find a suitable solution to meet the grid load and the charging and discharging requirements of electric vehicles. The value is between 0 and 1. The value is 2. The value is 2. , The value is between 0 and 1.

[0066] In this embodiment, in step S6, the formula Calculate the obtained Electric vehicles Update location at the moment .

[0067] Example 2

[0068] A device for implementing VSG group control in a V2G system, comprising: a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; wherein:

[0069] The memory is used to store computer programs;

[0070] The processor is configured to execute, by running a program stored in the memory:

[0071] Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles .

[0072] By minimizing the objective function, we can obtain Electric vehicles Power distribution at each moment .

[0073] According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Build constraints.

[0074] According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time .

[0075] According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time .

[0076] Passing speed Get the first Electric vehicles Update location at the moment .

[0077] Example 3

[0078] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the computer program implements:

[0079] Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles .

[0080] By minimizing the objective function, we can obtain Electric vehicles Power distribution at each moment .

[0081] According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Build constraints.

[0082] According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time .

[0083] According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time .

[0084] Passing speed Get the first Electric vehicles Update location at the moment .

[0085] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for implementing VSG group control in a V2G system, characterized in that: include: S1. Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles ; S2. By solving the objective function minimization, we can get Electric vehicles Power distribution at each moment ; S3. According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Construct constraints; S4. According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time ; S5. According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time ; S6. Passing speed Get the first Electric vehicles Update location at the moment ; S7. The VSG control module of the electric vehicle will update the position As the issued Control instructions for electric vehicles.

2. The method for implementing VSG group control in a V2G system according to claim 1, characterized in that: The objective function in step S2 The solution formula for minimizing is as follows: In the formula, is the number of time steps in the optimization cycle, for The load deviation weight at the moment, for The weight of unmet demand at the moment, is the total number of electric vehicles, For the The charging and discharging requirements of electric vehicles, is the penalty weight, For the penalty item, ,in is the maximum limit of power, The minimum limit for power.

3. The method for implementing VSG group control in a V2G system according to claim 1, characterized in that: In step S3, according to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Methods for constructing constraints include: S31. By formula Build The permissible range of power distribution for electric vehicles, For the The minimum supported power of an electric vehicle, For the The maximum supported power of an electric vehicle; S32. By formula Constructing grid load balancing constraints; S33. Through the formula Construct the battery state constraint, where For the Electric vehicles Battery status at all times, is the time step, is the battery capacity, , For the The minimum supported SOC of an electric vehicle, For the The maximum supported SOC of an electric vehicle.

4. The method for implementing VSG group control in a V2G system according to claim 1, characterized in that: In step S4, Electric vehicles Power distribution at each moment Bring it into the particle swarm optimization algorithm and randomly generate Electric vehicles The speed of time .

5. The method for implementing VSG group control in a V2G system according to claim 1, characterized in that: In step S4, the formula Solve the objective function of minimum power allocation, where For the Electric vehicles Power distribution at all times.

6. The method for implementing VSG group control in a V2G system according to claim 4, characterized in that: In step S5, the formula is: Calculate the first Electric vehicles The speed of time , where is the inertia weight, is the individual learning factor, is the social learning factor, , are all random numbers, For the Electric vehicles in The location at the moment, is the global best position.

7. The method for implementing VSG group control in a V2G system according to claim 6, characterized in that: The value is between 0 and 1. The value is 2. The value is 2. , The value is between 0 and 1.

8. The method for implementing VSG group control in a V2G system according to claim 7, characterized in that: In step S6, the formula Calculate the obtained Electric vehicles Update location at the moment .

9. A device for implementing VSG group control in a V2G system, characterized in that: include: A processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; wherein: The memory is used to store computer programs; The processor is configured to execute, by running a program stored in the memory: Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles ; By minimizing the objective function, we can obtain Electric vehicles Power distribution at each moment ; According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Construct constraints; According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time ; According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time ; Passing speed Get the first Electric vehicles Update location at the moment .

10. A computer-readable storage medium, characterized in that: The computer readable storage medium stores a computer program, which, when executed by a processor, implements: Collection Electric vehicles Battery status at all times , Expected grid load at time , No. Charging and discharging requirements of electric vehicles ; By minimizing the objective function, we can obtain Electric vehicles Power distribution at each moment ; According to Electric vehicles Power distribution at each moment , No. Electric vehicles Battery status at all times Construct constraints; According to Electric vehicles Power distribution at each moment Get the first Electric vehicles The speed of time ; According to Electric vehicles The speed of time Update speed, get Electric vehicles The speed of time ; Passing speed Get the first Electric vehicles Update location at the moment .

Images