Congestion Management Considering Wind Energy Sources Using Evolutionary Algorithm

Abstract

It is necessary to maintain power system security within a reasonable limit without harming the electric power supply in an emerging electricity market. Power systems are said to be congested when power transmission reaches beyond its limits. Therefore, in a deregulated power system environment, the system operator must look after the power transactions made by market parties. In this article, a novel congestion management method considering wind energy sources is introduced. The proposed congestion management technique is constructed considering the calculation of bus sensitivity factor and generator sensitivity factor. The bus sensitivity factor is used for finding the optimal location of a wind farm. The most sensitive generators are identified to reschedule their output by using the generator sensitivity factor. The artificial bee colony algorithm and particle swarm optimization techniques are applied to compare the generator rescheduling with earlier literature for congestion management. The proposed method has been tested on the 39-bus New-England test system to investigate the effectiveness of the proposed approach of wind farm integration for congestion management.