Improvement of Economic Aspect of Power Network Congestion Management by Swarm Intelligence based Multi-objective Algorithm

摘要

This paper presents a methodology based on a rescheduling algorithm for congestion constrained cost optimization in Particle Swarm Optimization environment. For proper maintenance of security and reliability, the congestion level of lines should be restricted to a stipulated value considering stability and demand constraints. The algorithm, proposed in this paper is capable of limiting line congestion with a minimum management charge without any load curtailment and installation of FACTS devices and it also provides better operating conditions in respect of voltage profile, total line loss and security for the system during contingency. For contingency selection and ranking, a Line Loading Index has also been proposed in this paper. A comparative analysis considering conventional cost optimization has also been presented in this paper which shows the applicability of the algorithm to minimize congestion management cost .It has also been shown that the implementation of the proposed methodology can offer a net saving of congestion cost which may appear as social welfare for the market participants. The proposed algorithm has been shown to be tested on IEEE 30 bus test system and the results obtained, looked promising.