Multi-objective particle swarm optimization for transient secure congestion management

Congestion is a condition in power systems operation in which some transmission lines become fully loaded. This problem intervene considerable amount of extra cost and increase burdens of power market participants. To alleviate congestion, the operator of power system pays participants to modify their active power generation or consumer side demand. This change in operating point would put the power system in the peril and the stability margins would drop because of the increase in participation of critical generators and load demand. Considering security margins as secondary function could maintain power system from instability points by restraining participation of generators and demands. In this paper a multi-objective version of particle swarm optimization is employed to find Pareto solutions of novel secure congestion management in which congestion management cost and Corrected Transient Energy Margin are considered as two competing objective functions. The proposed method has been tested on the New-England power system to validate the efficacy of proposed method.