Reservoir operation using a robust evolutionary optimization algorithm

Jafar Y Al-Jawad, Tiku T Tanyimboh

Research output: Contribution to journalArticle

Abstract

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.

LanguageEnglish
Pages275-286
Number of pages12
JournalJournal of Environmental Management
Volume197
Early online date7 Apr 2017
DOIs
Publication statusPublished - 15 Jul 2017

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Water
water demand
Drought
Evolutionary algorithms
Dams
Managers
water storage
low flow
dam
drought
water
methodology
policy

Keywords

  • evolutionary optimization algorithm
  • resevoir operation policy
  • mutlipurpose reservoir system
  • resevoir drawdown limits
  • self-adaptive recombination
  • environmental water management

Cite this

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Reservoir operation using a robust evolutionary optimization algorithm. / Al-Jawad, Jafar Y; Tanyimboh, Tiku T.

In: Journal of Environmental Management, Vol. 197, 15.07.2017, p. 275-286.

Research output: Contribution to journalArticle

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