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.

中文翻译：

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通过开发角马群优化 (DWHO) 来预测最佳水力发电，帮助优化水资源管理

为能源生产提供清洁水尤为重要。由于水资源有限，水力发电在当今世界社会面临着问题。鉴于这个问题，本研究的目的是调查水资源的优化管理及其对优化水力发电的影响。这项研究的创新之处在于使用新版本的开发角马群优化（DWHO）来预测水力发电量。该算法解决了优化问题，提高了水库调度发电结果的准确性。这项研究的结果表明，所开发的算法具有最高的收敛速度，并利用最耗时的数学过程来达到全局解，并防止陷入局部解。与功率估计相关的结果表明，DWHO 方法比其他对比算法多产生约 17% 的电量。此外，最高的可靠性指数为89.7%，弹性指数为68.1%，最低的脆弱性指数为12.8%，属于DWHO方法。