The Implementation of a New Optimization Method for Hydropower Generation and Multi-Reservoir Systems

Abbas Moghani () and Hojat Karami ()
Additional contact information
Abbas Moghani: Semnan University
Hojat Karami: Semnan University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 5, No 7, 1735 pages

Abstract: Abstract This research tries to find the best operation strategies for a reservoir system with the Flow Direction Algorithm (FDA), which was recently introduced. This study evaluates the implementation of the FDA, for the first time, for optimizing the hydropower operation of the Karun-4 reservoir in Iran for 106 months (from October 2010 to July 2019) and for the multi-reservoir systems for 12 months. Multi-Reservoir systems which are hypothetical 4 and 10-reservoir systems are studied to demonstrate the effectiveness and robustness of the algorithms. The results are compared to those of the three most commonly used evolutionary algorithms, namely the Particle Swarm Optimization Algorithm (PSO), the Weed Algorithm (WA), and the Genetic Algorithm (GA). The multi-reservoir results indicated that the absolute optimal solution was 308.292 in the four-reservoir benchmark system (FRBS) and 1194.441 in the ten-reservoir benchmark system (TRBS), and according to these results, FDA outperformed three other algorithms. In the Karun-4 reservoir, the best approach was chosen with the analytical hierarchy process (AHP) method, and according to the results, the FDA outperformed PSO, WA, and GA. The reliability percentage for FDA, PSO, WA, and GA was 95%, 86%, 78%, and 64%, respectively. The average optimal objective function value generated by FDA was 0.138, compared with PSO, WA, and GA, with the values of 0.322, 0.631, and 1.112, respectively, being better. The hydropower produced by FDA was more than three other algorithms in less time, with the lowest coefficient of variation value, which demonstrates the power of the FDA.

Keywords: Reservoir optimization; Hydropower; Flow direction algorithm; Evolutionary algorithm; Water resource management (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11269-024-03762-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:waterr:v:38:y:2024:i:5:d:10.1007_s11269-024-03762-7

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11269

DOI: 10.1007/s11269-024-03762-7

Access Statistics for this article

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) is currently edited by G. Tsakiris

More articles in Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA) from Springer, European Water Resources Association (EWRA)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().