A Multi-Objective Contingency Constrained Optimal Power Flow Based on Composite Security Index Using Genetic Algorithm and Newton Method

Abstract

Market economic constraints in the deregulated environment may force the power system to operate closer to its security limits there by decreasing the overall security margins. Efforts are needed to check the security before a set of transactions is accepted and to take preventive or corrective control actions as soon as these are deemed insufficient. This paper proposes a multi-objective contingency constrained optimal power flow to enhance the system security as well as to ensure the economic operation of the system. In order to reduce the high dimensionality of contingency constrained optimal power flow, only the critical contingencies are identified with the help of the developed composite security index and the corresponding constraints are used for the problem formulation. The composite security index which is a function of both power flow and bus voltage limit violations gives an accurate differentiation between the secure and non-secure states of the power system. Weight based Genetic algorithm is used as the optimization tool and the results obtained are validated using the conventional Newton method of optimization. The effectiveness of the method is tested on a practical Indian utility 62 bus system.