Research on an Energy-Harvesting System Based on the Energy Field of the Environment Surrounding a Photovoltaic Power Plant

Bin Zhang, Binbin Wang, Hongxi Zhang, Abdelkader Outzourhit, Fouad Belhora, Zoubir El Felsoufi, Jia-Wei Zhang and Jun Gao ()
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Bin Zhang: School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China
Binbin Wang: School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China
Hongxi Zhang: School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China
Abdelkader Outzourhit: Faculty of Sciences Semlalia, Cadi Ayyad University, Bd Prince Moulay Abdellah, Marrakech 40000, Morocco
Fouad Belhora: Laboratory of Engineering Sciences for Energy (LabSIPE), National School of Applied Sciences, Chouaib Doukkali University, El Jadida 24000, Morocco
Zoubir El Felsoufi: L’Ecole Supérieure de Technologie Sidi Bennour (ESTSB), Chouaib Doukkali University, El Jadida 24000, Morocco
Jia-Wei Zhang: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China
Jun Gao: School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China

Energies, 2025, vol. 18, issue 14, 1-20

Abstract: With the large-scale global deployment of photovoltaics (PV), traditional monitoring technologies face challenges such as wiring difficulties, high energy consumption, and high maintenance costs in remote or complex terrains, which limit long-term environmental sensing. Therefore, energy-harvesting systems are crucial for the intelligent operation of photovoltaic systems; however, their deployment depends on the accurate mapping of wind energy fields and solar irradiance fields. This study proposes a multi-scale simulation method based on computational fluid dynamics (CFD) to optimize the placement of energy-harvesting systems in photovoltaic power plants. By integrating wind and irradiance distribution analysis, the spatial characteristics of airflow and solar radiation are mapped to identify high-efficiency zones for energy harvesting. The results indicate that the top of the photovoltaic panel exhibits a higher wind speed and reflected irradiance, providing the optimal location for an energy-harvesting system. The proposed layout strategy improves overall energy capture efficiency, enhances sensor deployment effectiveness, and supports intelligent, maintenance-free monitoring systems. This research not only provides theoretical guidance for the design of energy-harvesting systems in PV stations but also offers a scalable method applicable to various geographic scenarios, contributing to the advancement of smart and self-powered energy systems.

Keywords: energy field distribution; photovoltaic power plant; wind field simulation; irradiance simulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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