Neuro fuzzy load frequency control in a competitive electricity market using BFOA tuned SMES and TCPS

Abstract

This paper addresses the design of Load frequency control in a competitive electricity market with a practical viewpoint. The restructure of vertically integrated power system into unbundled power system components as led to the emergence of new companies for Generation, transmission and Distribution of power. The conventional two-area power system is modified to study the effects of the bilateral contracts of companies on the system dynamics. Load frequency control is used to minimize the frequency oscillations and tie line power deviations. To stabilize the frequency oscillations Superconducting Magnetic Energy Storage device (SMES) is connected at the terminal side of a area and Thyristor Controlled Phase Shifter (TCPS) connected in series with the tie line. The parameters of SMES and TCPS were optimized using Bacterial Foraging Optimization Algorithm (BFOA). This paper uses Artificial Neuro Fuzzy Inference System (ANFIS) control and the results are compared with the conventional integral controller.