Mitigating congestion by optimal rescheduling of generators applying hybrid PSO–GWO in deregulated environment

Abstract

AbstractDeregulation in power system and increased power demand has introduced congestion in power system. With the depletion of fossil fuels, power sector has turned towards incorporation of the Renewable Energy Systems through private generators. This paper focuses on the non-cost-free method to mitigate congestion by rescheduling the generators for their active power output. The rescheduling is done in such a way that the cost of rescheduling is minimum. This paper presents a new method to merge two tested algorithms Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) to generate a new hybrid algorithm, HPSOGWO. The active power output is rescheduled to mitigate congestion with minimum cost of rescheduling. The priority of participating generators in rescheduling is set by generator sensitivity factor and its output is optimized by proposed HPSOGWO. The applied algorithm has reduced the rescheduled power to 16% less as done by GWO. HPSOGWO has moderated the congestion cost to 25% less as compared to GWO. The effectiveness of proposed HPSOGWO algorithm is validated on standard IEEE 30 bus system and results confirms the outperformance of proposed method over GWO and PSO in reducing congestion cost with reduction in power losses to mitigate congestion.