Comparing For Active Power Optimization With Classical Algorithm And Genetic Algorithm In Power Systems

For a long time, active optimization research and analysis of electric system isthe important content of its economic operation, which has important theoreticalreference and practical significance in ensuring the safety of the economic operationof electric system.This paper, in the background of the development feathers of modern electricsystem active optimization, takes the active optimization problem as the researchobject with classic method and genetic algorithm as the main research methods ofactive optimization. Not only the admittance matrix method of the classic activeoptimization and two kinds of network loss rate in Jacobi matrix method areanalyzed and derived in detail, but also the simplified algorithm of Jacobi matrix isdeduced. Meanwhile impedance matrix method derived net loss ratio increasedslightly. And the respective characteristics of the three algorithms are compared witheach other. This article also analyzes the application of genetic algorithm in activeelectric system optimization, which after improved is applied to active electricsystem optimization. The classic method of active optimization and improvedgenetic algorithm is applied to the examples IEEE-14node, and the IEEE-30node inthe paper. Through feasibility verification and comparison, this paper verifies theeffectiveness of the improved genetic algorithm in active optimization.