Chaotic Particle Swarm Optimization for Congestion Management in an Electricity Market

Congestion management is one of the major tasks performed by system operators (SOs) to ensure the operation of transmission system within operating limits. To permit smooth and quality flow of power the problem of congestion has to be solved. The congestion in the transmission line will be removed by generation rescheduling with the cost involved in the rescheduling process should be minimized. T he literature, classical optimization techniques were applied to solve this problem. The main drawbacks of the classical optimization techniques are higher computation time requirement, nondifferentiable characteristics of objective function and inferior quality of solutions. To overcome the above mentioned problems, heuristic optimization techniques are widely used. In our project presents Chaotic Particle Swarm Optimization (CPSO) based Congestion Management by optimal rescheduling of active powers of generators. In the proposed method, generators are selected based on their sensitivity to the congested line for efficient utilization. The task of optimally rescheduling the active powers of the participating generators to reduce congestion in the transmission line is attempted by CPSO and conventional PSO. The CPSO and PSO algorithms are tested on the IEEE 30-bus system. Compared with CPSO and PSO, CPSO can better perform the optimal rescheduling of generators to relieve congestion in the transmission line.