Predicting optimal hydropower generation with help optimal management of water resources by Developed Wildebeest Herd Optimization (DWHO)
Xiaojun Ren, Yuan Zhao, Dongmin Hao, Yueqiang Sun, Shaochun Chen, Fatemeh Gholinia
Abstract
Providing clean water for energy generation is of particular importance. Due to limited water resources, hydropower generation is facing problems in today’s world societies. Due to this issue, the purpose of this study is to investigate the optimal management of water resources and its impact on optimal hydropower generation. The innovation of this research is the use of a new version of Developed Wildebeest Herd Optimization (DWHO) to forecast hydropower generation. This proposed algorithm solves optimization problems and increases the accuracy of the results obtained for reservoir operation to generate power. The results of this study showed that the developed algorithm has the highest convergence speed and utilizes minimum time-consuming mathematical processes to reach the global solution and prevents trapping in local solutions. The results related to the estimation of power showed that the DWHO method produces about 17% more electricity than other compared algorithms. Also, the highest reliability index 89.7% and resilience index 68.1% and the lowest vulnerability index 12.8% belong to the DWHO method.