Alleviation of line congestion using Multiobjective Particle Swarm Optimization

This paper presents a methodology based on Particle Swarm Optimization technique for rescheduling of generation patterns to manage congestion in contingent power networks. In deregulated systems, line congestion attract additional penalties which add on to the overall operational cost to be incurred by the Independent System Operators (ISO), apart from causing limit violations, and stability problems. Thus, limiting the congestion level of lines and restricting power flows within the safe limits is important from stability as well as economy point of view. The algorithm proposed in the present paper uses a Standard Sensitivity Index to identify the congested zone(s) in a large power network and then adopt corrective actions for limiting line congestion at the cost of a nominal rescheduling cost without any load curtailment and installation of FACTS devices. It has been demonstrated that the proposed method can reduce congestion even below the minimum level obtained from the conventional cost optimization results. It has been depicted that the methodology on application can provide better operating conditions in respect of improvement of bus voltage profile. The efficiency of the proposed methodology has been tested on a IEEE 30 bus benchmark system and the results look promising.