Optimal Rescheduling of Active Power Generation Under Congestion Management Using Particle Swarm Optimization

Abstract

The restructuring of the electricity industry in the word has made the problem of transmission congestion increasingly significant. It aggravates the smooth functioning of competitive markets and typically high costs are associated with it, which have to be eventually borne by the consumers. Therefore, investigation of techniques for congestion-free wheeling of power is of paramount interest. This thesis presents a congestion management (CM) algorithm by optimal rescheduling of active powers of generators which minimize the redispatch cost of participating generators satisfying power balance, generator operating limit and line flow limits constraints while managing congestion effectively. Contributions made in this thesis are twofold. Firstly a technique for optimum selection of participating generators has been introduced using generator sensitivities to the power flow on congested lines. Secondly it proposes an algorithm based on particle swarm optimization (PSO) which minimizes the deviations of rescheduled values of generator power outputs from scheduled levels. The effectiveness of the proposed methodology has been analyzed on modified IEEE 30 and modified IEEE 57-bus system. The thesis concludes with a set of recommendations for future work.