This paper introduces an innovative metaheuristic approach combining the Whale Optimization Algorithm with Differential Evolution and local search (WOA-DE-LS) for solving power system Economic Dispatch (ED) challenges. The proposed methodology synthesizes the global exploration capabilities of WOA, the enhanced exploitation mechanisms of DE, and the refinement properties of local search to achieve an optimal balance between diversification and intensification. The algorithm’s performance is assessed on ED problems with various complexity levels, taking into account real operational limitations such as valve point constraints, restricted operating regions, and transmission losses. Comprehensive numerical experiments are conducted on three benchmark cases: a 20-unit system with quadratic cost functions, a 6-unit system incorporating valve point effects, and a 15-unit system with restricted operating zones. These systems represent diverse scenarios of increasing complexity in power system optimization. Comparative analyses show that WOA-DE-LS outperforms existing techniques, including conventional lambda-iteration methods and recent metaheuristic approaches, regarding both solution accuracy and computational efficiency. The proposed algorithm achieves optimal solutions for the conventional 20-unit system and demonstrates remarkable effectiveness when handling complex scenarios featuring valve point effects and restricted operating regions. These findings validate the capability of WOA-DE-LS in addressing ED challenges across various power system scales.