Improved Multi-objective Butterfly Optimization Algorithm and its Application in Cascade Reservoirs Optimal Operation Considering Ecological Flow

Zhangling Xiao, Mingjin Zhang (), Zhongmin Liang (), Jian Wang, Yude Zhu, Binquan Li, Yiming Hu, Jun Wang and Xiaolei Jiang
Additional contact information
Zhangling Xiao: Tianjin Research Institute for Water Transport Engineering, M.O.T.
Mingjin Zhang: Tianjin Research Institute for Water Transport Engineering, M.O.T.
Zhongmin Liang: Hohai University
Jian Wang: Tianjin Research Institute for Water Transport Engineering, M.O.T.
Yude Zhu: Tianjin Research Institute for Water Transport Engineering, M.O.T.
Binquan Li: Hohai University
Yiming Hu: Hohai University
Jun Wang: Hohai University
Xiaolei Jiang: Yangzhou University

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 12, No 17, 4803-4821

Abstract: Abstract Traditional reservoir operations often take power production as the main purpose. However, blindly maximizing power production will prompt the reservoirs to work continuously at high water levels, leading to lower water release and possible damage to the river ecosystem. In this paper, a multi-objective optimal operation model was established for a cascade reservoir system, with the goals of maximizing power production and ecological benefit. The ecological benefit was defined based on a suitable interval of ecological flow, which was calculated by the Tennant and flow duration curve methods. To efficiently solve the model, a multi-objective butterfly optimization algorithm was proposed by coupling the improved initial population strategy, dynamic switching probability strategy, archive elite solution-guided evolution, and polynomial mutation strategy. This algorithm was compared with three popular multi-objective optimization algorithms on benchmark functions and a cascade reservoir operation problem in the lower reaches of the Yalong River. Results showed that the proposed algorithm achieved the maximum hydropower production, with 82.5, 76.4 and 64.2 billion kW‧h in the wet, normal and dry years. It also obtained the highest ecological benefit values, which were 0.76, 0.80 and 0.86 in the wet, normal and dry years, respectively. The proposed algorithm has the potential to solve multi-objective optimization problems. Under different inflow scenarios, a certain competitive relationship between targets was witnessed. As the decrease of inflow, the competition tended to intensify. Graphical Abstract

Keywords: Multi-objective butterfly optimization algorithm; Cascade reservoir operation; Ecological flow calculation; Yalong River (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1007/s11269-024-03889-7 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:12:d:10.1007_s11269-024-03889-7

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

DOI: 10.1007/s11269-024-03889-7

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 ().