Adaptive Hybrid Fuzzy PI-LQR Optimal Control using Artificial Immune System via Clonal Selection for Two-Area Load Frequency Control

Abstract

Load frequency control (LFC) problem has been a foremost issue in electrical power system operation and is becoming more important recently with growing size, changing structure, and complexity in interconnected power systems. In general, LFC system utilizes simple proportional integral (PI) controller. However, due to the PI control parameters are commonly adjusted based on classical or trial-error method (TEM), it is incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios in a multi-area power system. This paper introduces a novel control scheme for load frequency control (LFC) using hybrid fuzzy proportional integral (fuzzy PI) and linear quadratic regulator (LQR) optimal control, where fuzzy logic control (FLC) is used to adjust the gains KP and KI of PI controller which called fuzzy PI in this paper, while the LQR optimal control method is employed to obtain the feedback gain KOP through Algebraic Riccati Equation (ARE). The merit of both control strategies is to tune their control feedback gains, which are KP, KI and KOP, regarding various system operating conditions. Artificial immune system (AIS) via clonal selection is utilized to optimize the membership function (MF) of fuzzy PI and weighting matrices Q and R of LQR optimal control in order to obtain their optimal feedback gains. To examine the efficacy of the proposed method, LFC of two-area power system model is utilized as a test system. The amalgamation of fuzzy PI-LQR is applied to improve the dynamic performance of two-area LFC. Other control schemes such as PI controller, hybrid PI controllerLQR, and hybrid fuzzy PI-LQR are also investigated to the studied a test system. The obtained simulation results show that the proposed method could compress the settling time and decrease the overshoot of LFC which is better than other approaches that are also employed to the tested system in this study.