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Reactive power optimization of power system based on improved genetic algorithm

Mingjun Chen

Open publisher page 10 citations

Abstract

Genetic algorithm is a evolution simulating optimal algorithm to solve complicated optimal problem with discrete varibles.This paper presents a new approach to optimal reactive power based on an improved genetic algorithm. This algorithm improves the method of coding, genetic operations and termination conditions. The proposed approach is applied to the IEEE 6 and IEEE 30 bus system. The simulation results show the improved genetic algorithm is reasonable and feasible.

About this research paper

What this paper is about

Genetic algorithm is a evolution simulating optimal algorithm to solve complicated optimal problem with discrete varibles.This paper presents a new approach to optimal reactive power based on an improved genetic algorithm. This algorithm improves the method of coding, genetic operations and termination conditions. The proposed approach is applied to the IEEE 6 and IEEE 30 bus system. The simulation results show the improved genetic algorithm is reasonable and feasible.

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OpenAlex reports 10 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Genetic algorithm is a evolution simulating optimal algorithm to solve complicated optimal problem with discrete varibles.This paper presents a new approach to optimal reactive power based on an improved genetic algorithm. This algorithm improves the method of coding, genetic operations and termination conditions. The proposed approach is applied to the IEEE 6 and IEEE 30 bus system. The simulation results show the improved genetic algorithm is reasonable and feasible.

Key concepts: Genetic algorithm, Meta-optimization, Electric power system, Computer science, Coding (social sciences), AC power, Mathematical optimization, Algorithm

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