A New Hybrid PSOGSA-TVAC Algorithm for Transmission Line Congestion Management in Deregulated Environment

In this manuscript, a modified nature-inspired algorithm (PSOGSA-TVAC) has been introduced for congestion management in a deregulated environment using the combination of time-varying acceleration coefficients of Particle Swarm Optimization (PSO-TVAC) and Gravitational Search Algorithm (GSA). The congestion is mitigated by most appropriately rearranging the generator's real power yields picked reliant on the measure of sensitivities of generator in respect to the congested line. The proposed algorithm is used to minimize rescheduling cost. PSOGSA-TVAC is tested with IEEE-Thirty Bus test system. The obtained results show its effectiveness as juxtaposing with CPSO (classical particle swarm optimization), PSO-TVIW (particle swarm optimization time-varying inertia weight) and PSO-TVAC (particle swarm optimization time-varying acceleration coefficients). The simulation/programming has been performed on MATLAB R2016a.