MULTI-OBJECTIVE NON-DOMINATED SHORTING GENETIC ALGORITHM-II FOR EXCITATION AND TCSC-BASED CONTROLLER DESIGN

Sidhartha Panda

   Non-Dominated Sorting in Genetic Algorithms-II (NSGA-II) is a popular non-domination based genetic algorithm for solving multi-objective optimization problems. This paper investigates the application of NSGA-II technique for the design of a Thyristor Controlled Series Compensator (TCSC)-based controller and a power system stabilizer. The design objective is to improve both rotor angle stability and system voltage profile. The proposed technique is applied to generate Pareto set of global optimal solutions to the given multi-objective optimization problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented and compared with a conventionally designed power system stabilizer under various loading conditions and disturbances to show the effectiveness and robustness of the proposed approach.

Keywords: multi-objective optimization, non-dominated shorting genetic algorithm, pareto solution set, thyristor controlled series compensator, power system stabilizer, power system stability

[full-paper]