Publication

Abstract : This paper proposes a Binary whale optimization algorithm integrated with an enhanced lambda iteration method (BWOA-ELI) to effectively solve the dynamic unit commitment and economic load dispatch (UC-ELD) problem in power system operations. In this approach, the binary whale optimization algorithm (BWOA) is employed to obtain an effective unit commitment schedule, while the enhanced lambda iteration (ELI) method determines the optimal power dispatch. The algorithm rigorously incorporates realistic and complex operational constraints such as prohibited operating zones, ramp rate limits, startup and shutdown costs, power balance, and spinning reserve requirements, ensuring feasible and practical generation schedules. The performance of BWOA-ELI is validated on two benchmark systems—the IEEE 57-bus 7-unit system and a 26-unit system—over a 24-hour scheduling horizon. Comparative analysis with established binary metaheuristic-based methods, including binary grey wolf optimization-ELI (BGWO-ELI), binary bat algorithm-ELI (BBA-ELI), binary crow search algorithm-ELI (BCSA-ELI), and binary enhanced particle swarm optimization-ELI (BEPSO-ELI), demonstrate that BWOA-ELI consistently achieves superior results in minimizing total generation cost and exhibiting enhanced convergence stability across multiple independent runs, due to its binarization technique, enhanced dispatch solver, and advanced constraint handling above previous BWOA applications. Furthermore, the proposed method strikes an effective balance between computational efficiency and solution accuracy, making it a robust and practical optimization tool for addressing complex and dynamic UC-ELD problems in modern power system planning and operation.