Yufei Wang , Jia-Wei Zhang , Kaiji Qiang , Runze Han , Xing Zhou , Chen Song , Bin Zhang , Chatchai Putson , Fouad Belhora , Hajjaji Abdelowahed
{"title":"基于物联网的绿色智能光伏系统在极端气候条件下实现能源可持续发展","authors":"Yufei Wang , Jia-Wei Zhang , Kaiji Qiang , Runze Han , Xing Zhou , Chen Song , Bin Zhang , Chatchai Putson , Fouad Belhora , Hajjaji Abdelowahed","doi":"10.1016/j.gloei.2024.11.006","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":36174,"journal":{"name":"Global Energy Interconnection","volume":"7 6","pages":"Pages 836-856"},"PeriodicalIF":1.9000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"IoT-based green-smart photovoltaic system under extreme climatic conditions for sustainable energy development\",\"authors\":\"Yufei Wang , Jia-Wei Zhang , Kaiji Qiang , Runze Han , Xing Zhou , Chen Song , Bin Zhang , Chatchai Putson , Fouad Belhora , Hajjaji Abdelowahed\",\"doi\":\"10.1016/j.gloei.2024.11.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":36174,\"journal\":{\"name\":\"Global Energy Interconnection\",\"volume\":\"7 6\",\"pages\":\"Pages 836-856\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Energy Interconnection\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2096511724001087\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Energy Interconnection","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096511724001087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
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 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.