A modified adaptive beluga whale optimization based on spiral search and elitist strategy for short-term hydrothermal scheduling

Short-term hydrothermal scheduling is a complex dynamic nonlinear optimization problem which considers various hydropower constraints. In this study, an adaptive beluga whale optimization method based on spiral search and elitist strategy is proposed to solve this complex problem. The proposed method has three main advantages: First, an adaptive parameter strategy based on a cosine function achieves a better balance between exploration and exploitation. Second, the spiral search and elite strategy guides search agents search for focused areas and effectively narrows the scope of the invalid search space. Third, instead the penalty function method, a feasibility-based selection comparison technique and heuristic strategy adopted to address complex constraints in STHS. In comparison to the results of benchmark functions from CEC 2015, ASEBWO generally demonstrates superior convergence accuracy when compared to the other seven algorithms. Additionally, the feasibility and effectiveness of ASEBWO are verified using two hydrothermal scheduling systems and compared with those of more than 10 algorithms. The comparison results demonstrate that ASEBWO achieves the best solution quality.