Electric power system multi-target reactive power optimization method based on DNA fuzzy genetic algorithm

A fuzzy genetic algorithm and power system technology, applied in the field of multi-objective reactive power optimization of power systems based on DNA fuzzy genetic algorithm, can solve problems such as multi-objective reactive power optimization, and achieve improved convergence speed and calculation accuracy, small static voltage The effect of stability margin and strong population diversity

Inactive Publication Date: 2018-05-18
ELECTRIC POWER RES INST OF GUANGXI POWER GRID CO LTD
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Problems solved by technology

[0005] Aiming at the deficiencies of the prior art, the present invention provides a multi-objective reactive power optimization method for power systems based on DNA Fuzzy Genetic Algorithm (DNA-FGA), which effectively solves the problems of the existing genetic algorithm in solving multi-objective reactive power optimization problems. defect

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  • Electric power system multi-target reactive power optimization method based on DNA fuzzy genetic algorithm
  • Electric power system multi-target reactive power optimization method based on DNA fuzzy genetic algorithm
  • Electric power system multi-target reactive power optimization method based on DNA fuzzy genetic algorithm

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[0017] The following describes the technical solutions of the present invention clearly and completely with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0018] The multi-objective reactive power optimization method of power system based on DNA fuzzy genetic algorithm provided by the present invention includes the following steps:

[0019] (1) Taking the minimum active power loss of the system and the maximum static voltage stability margin as the goal, considering the equality constraints and inequality constraints, a multi-objective reactive power optimization model of the power system is established.

[0020] ...

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Abstract

The invention discloses an electric power system multi-target reactive power optimization method based on a DNA fuzzy genetic algorithm, and relates to the electric power system multi-target reactivepower optimization technical field; the electric power system multi-target reactive power optimization method based on the DNA fuzzy genetic algorithm can code the control variables of the system in aDNA chain form, and can carry out genetic operations for individuals of population on said basis; the method combines the fuzzy control theory with the DNA genetic algorithm, can adjust the intersecting rate, the variation rate and inversion operation rate online according to the evolution condition of the algorithm, thus effectively improving the algorithm convergence speed and calculation precision; compared with a normal genetic algorithm, the DNA fuzzy genetic algorithm is faster in convergence speed, higher in calculation speed and stronger in population diversity when carrying out multi-target reactive power optimization, thus providing very well applicability for high dimension, multi-constraint and non-linear complex reality problems, such as electric power system reactive power optimization.

Description

Technical field [0001] The invention belongs to the technical field of power system multi-objective reactive power optimization, and in particular relates to a power system multi-objective reactive power optimization method based on DNA fuzzy genetic algorithm. Background technique [0002] Power system reactive power optimization is an important way to improve voltage quality, reduce network losses, and improve voltage stability. Mathematically, reactive power optimization is a typical nonlinear programming problem, which has the characteristics of nonlinearity, discontinuity, multi-variable and multi-constraint. [0003] As a global optimization method, genetic algorithm is an effective means to solve reactive power optimization problems. However, the binary coding method of conventional genetic algorithm cannot express rich genetic information, and during the evolution process, the crossover rate and mutation rate are fixed, resulting in When solving multivariable optimization ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H02J3/18
CPCH02J3/18H02J2203/20Y02E40/30
Inventor 刘光时孙志媛窦骞梁水莹刘默斯王晓明丘浩张翌晖
Owner ELECTRIC POWER RES INST OF GUANGXI POWER GRID CO LTD
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