Improved crisscross optimization algorithm-based multi-objective reactive power optimization method and system

Abstract

The present invention discloses an improved crisscross optimization algorithm-based multi-objective reactive power optimization method and system. The method comprises the steps of calculating target values of each particle in an initial population, wherein the target values at least comprise target values of an active power network loss, a voltage offset and a voltage stability margin; performing horizontal cross and vertical cross on the initial population so as to generate sub-generation W and sub-generation R; screening the sub-generation R to obtain an excellent particle population; and combining the initial population, the sub-generation W and the excellent particle population so as to generate a population pool, selecting a new generation of population by using non-dominated sorting and crowding distance, and outputting a final result when an iteration number of times is greater than a preset threshold. In the method, the active power network loss, voltage offset and voltage stability margin are all considered in reactive power optimization of the system, and the system is optimized by using the improved crisscross optimization algorithm, so that multi-objective reaction power optimization is realized, and the algorithm is less likely to optimize locally.

Description

technical field [0001] The present invention relates to the field of electric power systems, and more specifically, relates to a multi-objective reactive power optimization method and system based on an improved crossover algorithm. Background technique [0002] With the continuous expansion of the power system scale and the higher and higher requirements for system operation stability and economy, how to reduce network loss and improve voltage stability by optimizing the power system has attracted more and more attention from the industry. In power system operation, reactive power optimization is an important optimization problem. The reactive power optimization of traditional power systems mainly considers the reduction of active network losses during the power system optimization process. However, with the continuous development of power systems, only active network losses are considered. The reactive power optimization is obviously not able to meet the requirements. [...

AI Technical Summary

Problems solved by technology

In power system operation, reactive power optimization is an important optimization problem. The reactive power optimization of traditional power systems mainly considers the reduction of active network losses during the power system optimization process. However, with the continuous development of power systems, only active network losses are considered. The reactive power optimization can no longer meet the requirements

Images