Complementary operation optimization of cascade hydropower reservoirs and photovoltaic energy using cooperation search algorithm and conditional generative adversarial networks

Zhong-kai Feng, Xin Wang and Wen-jing Niu

Energy, 2025, vol. 328, issue C

Abstract: The rapid advancement of photovoltaic (PV) and other clean energy technologies has significantly increased their market share within power systems. However, these renewable energy sources are characterized by inherent volatility, intermittency, and unpredictability, which complicate the peak regulation of load demands. This paper presents a novel cascade hydro-solar complementary operation optimization method that leverages uncertain scenario generation to address these challenges. Initially, the conditional boundary equilibrium generative adversarial network model is used to dynamically capture the nonlinear relationships among solar output, irradiance, and solar angle. A clustering algorithm is then used to reduce these scenarios into a subset of representative output scenarios, which are integrated into the hydro-solar complementary operation model. To optimize the operation strategies, the novel cooperation search algorithm is selected as the optimizer. Engineering applications demonstrate that increased solar penetration exacerbates the impact of solar output uncertainty on the power grid. For example, in the spring, when the number of reservoirs is 4, the peak-valley difference of the spring load decreases from 2000.0 MW to 77.0 MW. The proposed method effectively mitigates these uncertainties across various scenarios by reducing peak load demands and enhancing residual load stability. Thus, a viable solution is provided for the complementary operation of cascade hydropower reservoirs and photovoltaic energy systems.

Keywords: Hydro-solar complementary operation; Conditional generative adversarial networks; Scenario generation; Cooperation search algorithm; Evolutionary algorithm (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S036054422502167X
Full text for ScienceDirect subscribers only

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:eee:energy:v:328:y:2025:i:c:s036054422502167x

DOI: 10.1016/j.energy.2025.136525

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().