EVOLUTIONARY HYBRID GENETIC-FIREFLY ALGORITHM FOR OPTIMIZING LFC REGULATION IN A DEREGULATED POWER SYSTEM

Abstract

This paper proposes an Evolutionary Hybrid Genetic-Firefly algorithm to optimize proportional (Kp), Integral (Ki), and Derivative (Kd) gains of a PID controller using IATE criteria as a performance criteria. In deregulated power system the maintenance of the real power balance between the GENCOs and DISCOs in an interconnected power system is an important issue and should be governed by ISO in order to meet the possible contracted bilateral transactions between the GENCOs and DISCOs in a secured manner. The present work focuses on regulating load frequency control ancillary service in a deregulated scenario with integration of potentially developing combined cycle gas fired power plants. The proposed control strategy is investigated on a two-area interconnected power system consisting of Hydro-Thermal unit in the area-I and Thermal-Gas unit in area-II. The main objective of optimization is to improve the dynamics of LFC such as improving of the transient response of frequency and tie-line power oscillations and to optimize the Power generated by various GENCOs according to the scheduled bilateral contracts. The simulation results show the PID controller tuned by the proposed Genetic-Firefly algorithm (GA-FA) exhibits a considerable improvement in dynamic performance of LFC.