A Fast Local Search Strategy Based on the Principle of Optimality for the Long-Term Scheduling of Large Cascade Hydropower Stations

Chao Wang, Zhiqiang Jiang (), Pengfei Wang and Yichao Xu
Additional contact information
Chao Wang: State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research
Zhiqiang Jiang: Huazhong University of Science and Technology
Pengfei Wang: Huazhong University of Science and Technology
Yichao Xu: Huazhong University of Science and Technology

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2024, vol. 38, issue 1, No 7, 137-152

Abstract: Abstract The objective of jointly optimizing the dispatching of cascade hydropower stations in the basin is to maximize economic benefits while ensuring the safe and stable operation constraints of power grids and hydropower stations. The existing joint optimization scheduling algorithms include dynamic programming algorithms and intelligent optimization algorithms. Among them, the progressive optimization algorithm (POA) as a representative of dynamic programming methods can effectively solve complex nonlinear constraint optimization problems. However, while it effectively addresses the issue of “dimensional disaster” in traditional dynamic programming, it also faces the challenge of “local convergence”. Although the intelligent optimization algorithm such as the differential evolutionary algorithm (DE) and the genetic algorithm (GA) can effectively handle large-scale complex constraint optimization problems, these algorithms rely on their own group evolution mechanism and lack a search strategy tailored to the mathematical mechanism of the joint scheduling model of cascade hydropower stations. Starting with the theoretical analysis of the two-stage problem of optimizing and dispatching cascade hydropower stations, this paper deduces the monotonicity principle of the two-stage optimization problem for power generation dispatch and proposes a local search strategy based on the monotonicity principle. By using the cascade reservoir group in the lower reaches of JinSha River as an example, the local search strategy for the two-stage optimization problem of power generation dispatch in cascade hydropower stations is validated. This strategy improves the convergence rate and solution accuracy of the algorithm, thereby achieving an efficient solution to the joint optimization dispatch problem of cascade hydropower stations.

Keywords: Cascade hydropower station; Joint optimal scheduling; Two-stage optimal problem; Monotonicity principle; Jinsha River; Local search policy (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11269-023-03658-y 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:1:d:10.1007_s11269-023-03658-y

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

DOI: 10.1007/s11269-023-03658-y

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 ().