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Review | Open Access

Research and practice on the intelligent photovoltaic power station in Yalong River Basin

Peng ZhangHaoyang Peng( )Kaizhi Xiong
Yalong River Hydropower Development Company, Co., Ltd., Chengdu 610051, China
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Abstract

With the expansion of the photovoltaic market scale and the complexity of the international geopolitical and economic landscape, an increasing number of countries are prioritizing the development of their indigenous photovoltaic industries to ensure energy security, enhance global industrial competitiveness, and increase domestic employment. This study first reviews the current development status of the photovoltaic industry and the evolutionary history of photovoltaic power stations. Second, in conjunction with the planning of an intelligent photovoltaic power station in the Yalong River Basin in China, this study proposes a conceptual framework, objectives, and overall architecture for the intelligent planning of photovoltaic power stations. Finally, based on practical experiments conducted at the Kela Photovoltaic Power Station with an installed capacity of 1.00 GW, this study introduces intelligent technologies for photovoltaic power stations, such as a digital twin platform and unmanned aerial vehicle (UAV) intelligent inspection. The results indicate that the intelligent construction of photovoltaic power stations enhances overall efficiency, enables unmanned management, maximizes economic benefits, improves the quality of photovoltaic power generation, reduces the curtailment rate of photovoltaic power stations, and increases the overall station revenue. This study provides a reference for the intelligent construction of photovoltaic power stations.

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Journal of Intelligent Construction
Article number: 9180100

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Cite this article:
Zhang P, Peng H, Xiong K. Research and practice on the intelligent photovoltaic power station in Yalong River Basin. Journal of Intelligent Construction, 2025, 3(3): 9180100. https://doi.org/10.26599/JIC.2025.9180100

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Received: 28 March 2025
Revised: 15 April 2025
Accepted: 21 April 2025
Published: 09 June 2025
© The Author(s) 2025.

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.