Reservoir operation using a robust evolutionary optimization algorithm

JOURNAL OF ENVIRONMENTAL MANAGEMENT

卷:197

Article

Al-Jawad, Jafar Y.¹  Tanyimboh, Tiku T.¹ 

[1] Univ Strathclyde Glasgow, Dept Civil & Environm Engn, 75 Montrose St, Glasgow G1 1XJ, Lanark, Scotland

关键词: Evolutionary optimization algorithm;    Reservoir operation policy;    Multipurpose reservoir system;    Reservoir drawdown limits;    Self-adaptive recombination;    Environmental water management;   

DOI  :  10.1016/j.jenvman.2017.03.081

来源: Elsevier

【 摘 要 】

In this research, a significant improvement in reservoir operation was achieved using a state-of-the-art evolutionary algorithm named Borg MOEA. A real-world multipurpose dam was used to test the algorithm's performance, and the target of the reservoir operation policy was to fulfil downstream water demands in drought condition while maintaining a sustainable quantity of water in the reservoir for the next year. The reservoir's performance was improved by increasing the maximum reservoir storage by 14.83 million m(3). Furthermore, sustainable water storage in the reservoir was achieved for the next year, for the simulated low flow condition considered, while the total annual imbalance between the monthly reservoir releases and water demands was reduced by 64.7%. The algorithm converged quickly and reliably, and consistently good results were obtained. The methodology and results will be useful to decision makers and water managers for setting the policy to manage the reservoir efficiently and sustainably. (C) 2017 Elsevier Ltd. All rights reserved.

【 授权许可】

Free