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Power grid structure optimization method based on genetic algorithm

A technology of grid grid and optimization method, applied in the field of grid grid optimization based on genetic algorithm, can solve problems such as easy to fall into local optimal solution, dimensional disaster, etc., to reduce the scale of feasible chromosome solution space, quickly obtain, reduce The effect of complexity

Pending Publication Date: 2021-04-27
STATE GRID ZHEJIANG ELECTRIC POWER CO LTD SHAOXING POWER SUPPLY CO
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Problems solved by technology

[0003] Modern heuristic algorithms such as genetic algorithm (Genetic algorithm, GA), simulated annealing (Simulated Algorithm, SA) algorithm, tabu search (Tabu search, TS) algorithm and ant colony algorithm (Ant Colony Algorithm, ACA) provide ideas for solving power grid planning problems , however, these optimization algorithms have limitations. When solving, they often appear "dimension disaster" and easily fall into local optimal solutions, and are only applicable to the planning of a single voltage level network

Method used

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  • Power grid structure optimization method based on genetic algorithm
  • Power grid structure optimization method based on genetic algorithm
  • Power grid structure optimization method based on genetic algorithm

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Embodiment 1

[0039] refer to figure 1 , which is the first embodiment of the present invention, this embodiment provides a method for optimizing the power grid frame based on genetic algorithm, including:

[0040] S1: Encoding the disconnected branches in the power grid to obtain the initial population.

[0041] Specifically, the encoding steps are as follows:

[0042] ①Assume that the number of closed branches is N, and the set formed by N closed branches is M;

[0043] ② Select a closed branch from the set M and disconnect it;

[0044] ③ Number the disconnected branch, and use the number of the disconnected branch as the gene number, and the chromosome length is N;

[0045] ④ The genes of each chromosome are encoded with random probability integers to form chromosomes and complete the encoding operation.

[0046]By repeating steps ①②③④20 times, the same number of chromosomes as the population size is generated to obtain the initial population.

[0047] Preferably, this embodiment ad...

Embodiment 2

[0081] In order to verify and explain the technical effect adopted in this method, this embodiment chooses the basic ant colony algorithm and adopts this method to conduct a comparative test, and compares the test results by means of scientific demonstration to verify the real effect of this method.

[0082] The basic ant colony algorithm has limitations. When solving, it often appears "dimension disaster" and easily falls into a local optimal solution, and it is only suitable for the planning of a single voltage level network.

[0083] In order to verify that this method can quickly obtain the global optimal solution and better compensation effect compared with the basic ant colony algorithm, in this embodiment, the basic ant colony algorithm and this method will be used to plan and compare the lines of the power grid system.

[0084] This embodiment is a 33-node power distribution system with a single power supply in the IEEE standard calculation example, and its original net...

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Abstract

The invention discloses a power grid structure optimization method based on a genetic algorithm, and the method comprises the steps: carrying out the coding of a disconnected branch of a power grid, and obtaining an initial population; the initial population generates a new generation of population through iterative selection, intersection and variation, and then the fitness of the new generation of population is calculated; when the fitness reaches the maximum value, stopping the iteration, and further obtaining the optimal fitness; constructing a power grid planning objective function based on a direct-current power flow model, constructing an adaptive model by combining the objective function and the optimal fitness, and optimizing a power grid structure according to the adaptive model. According to the method, the feasible chromosome solution space scale is reduced by using integer coding, the genetic operation of the original genetic algorithm is improved, the calculation efficiency of the genetic algorithm is improved, the globally optimal solution can be quickly obtained, and the complexity of a power grid structure is reduced.

Description

technical field [0001] The invention relates to the technical field of power grid optimization, in particular to a genetic algorithm-based power grid grid optimization method. Background technique [0002] Power grid planning is a complex optimization problem with the characteristics of multi-objective, uncertainty, nonlinearity and multi-stage. At present, many scholars at home and abroad have carried out in-depth research on this kind of problem and proposed many solutions , such as branch and bound method, relaxation method, cutting plane method, external approximation method, etc. [0003] Modern heuristic algorithms such as genetic algorithm (Genetic algorithm, GA), simulated annealing (Simulated Algorithm, SA) algorithm, tabu search (Tabu search, TS) algorithm and ant colony algorithm (Ant Colony Algorithm, ACA) provide ideas for solving power grid planning problems , however, these optimization algorithms have limitations. When solving, they often appear "dimension d...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06F30/27G06N3/12G06F113/04
CPCG06Q10/04G06Q50/06G06F30/27G06N3/126G06F2113/04
Inventor 赵淑敏杨刚陈俊胡大栋单林森
Owner STATE GRID ZHEJIANG ELECTRIC POWER CO LTD SHAOXING POWER SUPPLY CO
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