Study on Electric Automation with Reactive Optimization Based on TSGA in Power System

摘要

Focusing on electric automation with the reactive optimization for power system which is a nonlinear object with multiple variables and constraint conditions, the paper presents an optimal method based on Taboo Search and Genetic Algorithm, which inherits and develops the advantages of multiple search and high robust performance of Genetic Algorithm, and the high climbing ability of Taboo Search to improve the convergence performance and speed. The simulation for IEEE30 node system proves that the method introduced in the paper is appropriate and efficient in the field of electric automation.