October 31, 2024
Mohamad Reza Madadi

Mohamad Reza Madadi

Academic rank: Associate professor
Address: Department of Water Engineering, Faculty of Agriculture, University of Jiroft, Jiroft, Iran
Education: PhD. in Water Structures
Phone:
Faculty:

Research

Title
Optimization of hydropower energy generation by 14 robust evolutionary algorithms
Type Article
Keywords
Optimization, hydropower , evolutionary algorithms,
Researchers Mohamad Reza Sharifi, Saeid Akbarifard, Mohamad Reza Madadi, Kourosh Qaderi, Hossein Akbarifard

Abstract

The use of evolutionary algorithms (EAs) for solving complex engineering problems has been very promising, so the application of EAs for optimal operation of hydropower reservoirs can be of great help. Accordingly, this study investigates the capability of 14 recently-introduced robust EAs in optimization of energy generation from Karun-4 hydropower reservoir. The best algorithm is the one that produces the largest objective function (energy generation) and has the minimum standard deviation (SD), the minimum coefficient of variations (CV), and the shortest time of CPU usage. It was found that the best solution was achieved by the moth swarm algorithm (MSA), with the optimized energy generation of 19,311,535 MW which was 65.088% more than the actual energy generation (11,697,757). The values of objective function, SD and CV for MSA were 0.147, 0.0029 and 0.0192, respectively. The next ranks were devoted to search group algorithm (SGA), water cycle algorithm (WCA), symbiotic organism search algorithm (SOS), and coyote optimization algorithm (COA), respectively, which have increased the energy generation by more than 65%. Some of the utilized EAs, including grasshopper optimization algorithm (GOA), dragonfly algorithm (DA), antlion optimization algorithm (ALO), and whale optimization algorithm (WOA), failed to produce reasonable results. The overall results indicate the promising capability of some EAs for optimal operation of hydropower reservoirs.