Applying of Marine Predators Algorithm Linked with Reservoir Simulation Model considering Sedimentation for Reservoir Operation

Abstract

This paper proposes the Marine Predators algorithm (MPA) linked with the reservoir simulation model and considering sedimentation, in order to improve reservoir rule curves. The release criteria of the hedging rule (HR) and standard operating policy (SOP) were investigated in this study. The results showed that the patterns of the new optimal rule curves from the MPA technique considering sedimentation and using HR were practically useful in this study, as were the patterns of the new optimal rule curves using SOP and those of the existing rule curves. Furthermore, the new optimal rule curves using HR criteria were able to alleviate both water scarcity and excess water situations better than both existing rule curves and optimal rule curves using SOP in terms of minimal average water shortage. The new curves reduced minimal average water shortage by 53% and excess release water deficit by 19%, whereas the frequency of water shortage term was increased by 3%. The results of rule curves efficiency from MPA were higher than GA and FPA techniques in terms of providing solutions. There was a significant difference in the efficiency of water problem alleviation between considering and not considering sedimentation. It can be concluded that the MPA linked with reservoir simulation using HR criteria and considering sedimentation can be used to find optimal rule curve solutions effectively.

Optimizing Solution in Decision Supporting System for River Basin Management Consisting of a Reservoir System

“…However, for managing intricate reservoirs, these methods may be insufficient [33][34][35]. To overcome this limitation, metaheuristic algorithms like genetic algorithms (GA) [36,37], genetic programming (GP) [38,39], tabu search (TA) [40], Harris Hawks optimization (HHO) [41], wind-driven optimization (WDO) [42], firefly algorithm (FA) [43], flower pollination algorithm (FPA) [44,45], gray wolf optimizer [46], marine predator algorithm (MPA) [47], and others have been employed. These algorithms effectively locate the global optimum, offering diverse solutions.…”