Congestion management in a deregulated power system using NSGAII

Abstract

Congestion of the transmission corridors is a major issue in the open access regime, which is usually managed by rescheduling of generators and demands. The changes in schedule due to Congestion management (CM) may cause voltage stability margins to shrink to unacceptable levels. Voltage stability issues must, therefore, be considered during congestion management. Loading Margin (LM) between the voltage collapse point and the current power system operation point is employed as an index of voltage stability margin. This paper presents a novel multi-objective formulation of the CM problem in a pool model, with the competing objective functions of minimizing CM cost and maximizing LM. Non-dominated Sorting Genetic Algorithm II (NSGAII) is employed to achieve the best trade off among CM Cost and LM. Fuzzy decision maker is made use of to extract the best compromise non-dominated solution. The proposed method has been tested on 39-bus New England System and results show the efficacy of the proposed technique in minimizing the cost of congestion management and maintaining sufficient level of stability margin while alleviating congestion in the transmission lines. Compared with the other reported single-objective approach, the proposed algorithm has been found to perform better. The quality of the solution and convergence speed obtained by this establishes the efficacy of the proposed approach in solving multi-objective congestion management problem.