A Hybrid Grey Wolf Optimization Algorithm Using Robust Learning Mechanism for Large Scale Economic Load Dispatch with Vale-Point Effect

This paper proposes a new hybrid algorithm for grey wolf optimization (GWO) integrated with robust learning mechanism to solve the large-scale economic load dispatch (ELD) problem. The (RLGWO) imitates hunting behavior and social hierarchy of wolves in nature is reinforced by tolerance-based adjust searching direction opposite-based learning. technique could effectively prevent search agents from being trapped local optima also generate potential candidates obtain feasible solution. Several constraints power generators, such as generation limits, demand, valve-point loading effect, transmission losses, are considered practical operation. Five test systems used evaluate effectiveness robustness proposed solving ELD simulation results clearly reveal superiority feasibility RLGWO find better solutions terms fuel cost computational efficiency when compared previous literature.