Automatic Generation Control of Multi-Area Power System Using a Fuzzy Wavelet Neural Network Load Frequency Controller Combined With Shuffled Frog Leaping Algorithm

Abstract

In this paper, an auto tuned load frequency controller based on Fuzzy Wavelet Neural Network (FWNN) and Shuffled Frog Leaping Algorithm (SFLA) is employed to damp the deviations in frequency and tie line power due to load disturbances in a multi-area power system. Optimal tuning of FWNN parameters is very important to improve the design performance and achieving a satisfactory level of robustness, for a particular operation. In this work, a new systematic tuning method is developed for designing the FWNN load frequency controller. For this, the error between desired system output and output of control object is employed to tune the FWNN parameters. Tuning rule is accomplished based on SFLA approach by minimizing a compound of control error. To show the effectiveness of the proposed method, some numerical results are presented for a two area power system with considerations regarding governor saturation and the results are compared to the one obtained by a classic PI controller and a fuzzy load frequency controller. Moreover, the robustness of the proposed method is tested against change of parameters. The simulation studies show that the designed controller by proposed method has a very desirable dynamic performance, better operation and improved system parameters such as settling time and step response rise time even when the system parameters change.