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

摘要

Deregulation in power system and increased power demand has introduced congestion in power system. With the depletionof fossil fuels, power sector has turned towards incorporation of the Renewable Energy Systems through privategenerators. This paper focuses on the non-cost-free method to mitigate congestion by rescheduling the generators fortheir active power output. The rescheduling is done in such a way that the cost of rescheduling is minimum. This paperpresents 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 congestionwith minimum cost of rescheduling. The priority of participating generators in rescheduling is set by generator sensitivityfactor and its output is optimized by proposed HPSOGWO. The applied algorithm has reduced the rescheduledpower 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 theoutperformance of proposed method over GWO and PSO in reducing congestion cost with reduction in power lossesto mitigate congestion.