Investigating dam reservoir operation optimization using metaheuristic algorithms

Abstract The optimization of dam reservoir operations is the utmost importance, as operators strive to maximize revenue while minimizing expenses, risks, and deficiencies. Metaheuristics have recently been investigated extensively by researchers in management reservoirs. But animal-concept-based metaheuristic algorithm with Lévy flight integration approach has not used at Karun-4. This paper investigates operation using three unexplored metaheuristics: whale (WOA), Levy-flight WOA (LFWOA), Harris hawks (HHO). Utilizing a time series data set on hydrological climatic characteristics Karun-4 hydroelectric Iran, an analysis was conducted. objective functions constraints hydropower were examined throughout procedure. HHO produces best optimal value, least-worst average standard deviation (SD) scores 0.000026, 0.001735, 0.000520, 0.000614, respectively, resulting overall ranking mean (RM) score 1.5 Throughout duration test, optimized trends water release storage indicate that superior other metaheuristics. correlation variation (CV) 0.090195, LFWOA convergence rate (3.208 s) CPU time. Overall, it can be concluded most desirable performance terms optimization. Yet, current studies both generate positive comparable outcomes.