Optimal Active Power Rescheduling of Generators for Congestion Management Based On Big Bang-Big Crunch Optimization Using New Definition of Sensitivity

Restructuring of power systems and appearance and development of many electricity markets in all levels of power systems, introduce the congestion challenge of power transmission lines as a critical threat for power systems. Many studies have been attempted to present techniques for congestion management (CM). One of them is active power rescheduling of generators which has two steps. First step is optimum selection of generators on the basis of sensitivities of generator to power flow on congested line/lines. In this paper, the new definition of sensitivity is introduced based on the old definition of sensitivity that consists of cost factor. Next step of CM process is optimum rescheduling of generators power. In this paper, the optimization of rescheduling of generators power is performed based on Big Bang-Big Crunch (BB-BC) algorithm which is improved by Particle Swarm Optimization (PSO) method as Hybrid BB-BC (HBB-BC) optimization for the first time. Effectiveness of the results of proposed method has been tested on the 39-bus New England system and IEEE 30-bus and IEEE 118-bus systems.