IoT-based green-smart photovoltaic system under extreme climatic conditions for sustainable energy development

To realize carbon neutrality, there is an urgent need to develop sustainable, green energy systems (especially solar energy systems) owing to the environmental friendliness of solar energy, given the substantial greenhouse gas emissions from fossil fuel-based power sources. When it comes to the evol...

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Bibliographic Details
Main Authors: Yufei Wang, Jia-Wei Zhang, Kaiji Qiang, Runze Han, Xing Zhou, Chen Song, Bin Zhang, Chatchai Putson, Fouad Belhora, Hajjaji Abdelowahed
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-12-01
Series:Global Energy Interconnection
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Online Access:http://www.sciencedirect.com/science/article/pii/S2096511724001087
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Summary:To realize carbon neutrality, there is an urgent need to develop sustainable, green energy systems (especially solar energy systems) owing to the environmental friendliness of solar energy, given the substantial greenhouse gas emissions from fossil fuel-based power sources. When it comes to the evolution of intelligent green energy systems, Internet of Things (IoT)-based green-smart photovoltaic (PV) systems have been brought into the spotlight owing to their cutting- edge sensing and data-processing technologies. This review is focused on three critical segments of IoT-based green-smart PV systems. First, the climatic parameters and sensing technologies for IoT-based PV systems under extreme weather conditions are presented. Second, the methods for processing data from smart sensors are discussed, in order to realize health monitoring of PV systems under extreme environmental conditions. Third, the smart materials applied to sensors and the insulation materials used in PV backsheets are susceptible to aging, and these materials and their aging phenomena are highlighted in this review. This review also offers new perspectives for optimizing the current international standards for green energy systems using big data from IoT-based smart sensors.
ISSN:2096-5117