Small Signal Stability Constrained Optimal Power Flow using Genetic Algorithm

This paper presents a solving methodology for small signal stability constrained Optimal Power Flow (SSSC-OPF) using evolutionary genetic algorithm (GA) considering various objective functions under different contingency scenarios. The final goal of OPF is finding of optimal operating point of power system according to various constraints. By adding small signal stability constraint to the OPF problem, a preventive state for avoiding from small signal oscillatory instability is achieved. Henec, it can be guaranteed to damp electromechanical oscillations triggered by small disturbances in the system and return the operating point to the optimal condition. Two objective functions, namely minimization of total generation cost and expected-security cost subjected to the problem constraints have been considered and optimized by genetic algorithm. The proposed strategy enables to solve the SSSC-OPF problem and finds optimum operating points of the power system before and after the occurance of disturbance. The performance and effectiveness of the proposed method have been studied and simulated on the IEEE 9 and 24-bus test systems.