Gencos optimal strategic bidding with transmission constraints using particle swarm optimization

Abstract

This paper proposes an optimal strategic bidding with transmission congestion using Particle Swarm Optimization with Time varying acceleration coefficients (PSO-TVAC). A bilevel programming (BLP) technique is formulated in which upper level problem represents an individual generating company (Genco) profit maximization and the lower level represents the independent system operator's (ISO) market clearing problem with and without transmission congestion. The values of Transmission Congestion Distribution factors (TCDFs) are used to select redispatch of generators for congestion management with and without generator reactive power procurement. Numerical result on test system IEEE 30 bus is presented for illustration purpose and the results are compared with Particle swarm optimization (PSO), Particle Swarm Optimization with Time Varying Inertia Weight (PSO-TVIW) and Particle Swarm Optimization with Time Varying acceleration coefficients (PSO-TVAC) in terms of solution quality. The comprehensive experimental results prove that the PSO-TVAC is one among the challenging optimization methods which is indeed capable of obtaining higher quality solutions for the proposed problem.