ANT LION OPTIMIZER DUAL MODE FRACTIONAL ORDER PROPORTIONAL INTEGRAL CONTROLLER FOR MULTI AREA POWER SYSTEMS WITH RENEWABLE ENERGY SOURCES AND INTEGRATING ELECTRICAL VEHICLE CHARGING STATIONS

Abstract

The increasing penetration of renewable energy sources (RESs), electric vehicles (EVs), and rapidly varying load demands has introduced significant challenges in maintaining frequency stability in modern interconnected power systems. Conventional load frequency control (LFC) methods with fixed or inadequately optimized controller parameters often exhibit poor dynamic performance under such uncertain operating conditions. To address these challenges, this paper proposes an Ant Lion Optimizer (ALO)-based Dual-Mode Fractional-Order Proportional Integral (DMFOPI) controller for a three-area interconnected power system incorporating RESs and EV charging stations. For a comprehensive performance evaluation, conventional Proportional-Integral (PI), Dual-Mode PI (DMPI), Fractional-Order PI (FOPI), and the proposed DMFOPI controllers are optimally tuned using the ALO algorithm based on the Integral Square Error (ISE) performance criterion. The proposed controller is validated in the MATLAB/Simulink environment under step load disturbances, EV integration, and ±20% turbine time-constant variations. Simulation results demonstrate that the ALO-DMFOPI controller achieves superior frequency regulation with reduced frequency deviations, improved damping characteristics, shorter settling times, and enhanced disturbance rejection compared with the PI, DMPI, and FOPI controllers. The proposed controller achieves the minimum ISE value of 0.21836 and the lowest performance index (J = 0.1128), indicating its improved control effectiveness. Furthermore, the proposed controller maintains robust and reliable performance under both EV-connected and EV-disconnected operating conditions, as well as under turbine parameter uncertainties. The results confirm that the ALO-DMFOPI controller is an effective and robust solution for load frequency control in modern interconnected power systems with high penetration of renewable energy sources and electric vehicles.