بهینه سازی مدیریت انرژی و تبدیل در سیستم های چند مخزنی بر اساس الگوریتم های تکاملی

Concerning water and energy crisis, energy management and correct utilization of resources are important. In the present study, utilization of a multi-reservoir system was addressed with an approach to improve production of hydroelectric energy. For this purpose, Monarch Butterfly Algorithm (MBA), which is a new evolutionary algorithm, was used. Three periods of dry (1963–64), wet (1951–52) and normal (1985–86) conditions were considered in the operation of a 4-reservoir system. Results showed that MBA was capable of generating more energy as compared to Particle Swarm Optimization (PSO) algorithm and Genetic Algorithm (GA). For instance, MBA improved the accuracy of GA and PSO in generating energy by 1.16 and 0.88 percent in the wet year, 1.28 and 1.2 percent in the dry year and 1.34 and 0.88 percent in the normal year, respectively. Moreover, quality of the responses obtained from the MBA was better than those of the other two algorithms, because coefficients of variation of the responses in MBA were less.