Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

Kai Lun Chong, Sai Hin Lai, Ali Najah Ahmed, Wan Zurina Wan Zaafar, Ravipudi Venkata Rao, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-Shafie

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

In engineering and scientific disciplines, there are extensive Optimization Application Problems (OAPs) such as economic dispatch, structural design, and water resources. One of the major OAPs is the operation of dams and reservoirs to minimize the gap between water supply for irrigation and demand patterns such as hydropower generation. Drawing optimal operation for dams and reservoirs is often categorized as discontinuity, multimodality, non-differentiability and non-convexity. Classical mathematical programming-based methods for optimization might be inappropriate or unrealizable in drawing optimal operation rules for dam and reservoir operation. During the last two decades, new optimization methods-based on nature-inspired meta-heuristic algorithms (MHAs) have motivated hydrologists to investigate MHAs as better alternative optimization tools for identifying the optimal dam and reservoir operation rules. To solve the dam and reservoir-optimization applications better, this review presents the past, present, and prospective research directions using MHAs. The problem of dam and reservoir optimization requires a fundamental shift of focus towards enhancing not only the problem formulation and decomposition but also the computational efficiency of MHAs.

Original languageEnglish
Article number9335575
Pages (from-to)19488-19505
Number of pages18
JournalIEEE Access
Volume9
DOIs
Publication statusPublished - 2021

Keywords

  • Meta-heuristic algorithm
  • optimization
  • reservoir operation
  • water resources management

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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