全球能源互联网（英文）2023，Vol.6Issue(5)：567-591,25.DOI:10.1016/j.gloei.2023.10.005
混合光伏-温差系统 最大功率点跟踪技术最新综述:建模、方法和前景展望
State-of-the-art review of MPPT techniques for hybrid PV-TEG systems:modeling,methodologies,and perspectives
摘要
Abstract
The development of alternative renewable energy technologies is crucial for alleviating climate change and promoting energy transformation.Of the currently available technologies,solar energy has promising application prospects owing to its merits of being clean,safe,and sustainable.Solar energy is converted into electricity through photovoltaic(PV)cells;however,the overall conversion efficiency of PV modules is relatively low,and most of the captured solar energy is dissipated in the form of heat.This not only reduces the power generation efficiency of solar cells but may also have a negative impact on the electrical parameters of PV modules and the service life of PV cells.To overcome the shortcomings,an efficient approach involves combining a PV cell with a thermoelectric generator(TEG)to form hybrid PV-TEG systems,which simultaneously improve the energy conversion efficiency of the PV system by reducing the operating temperature of the PV modules and increasing the power output by utilizing the waste heat generated from the PV system to generate electricity via the TEGs.Based on a thorough examination of the literature,this study comprehensively reviews 14 maximum power point tracking(MPPT)algorithms currently applied to hybrid PV-TEG systems and classifies them into five major categories for further discussion,namely conventional,mathematics-based,metaheuristic,artificial intelligence,and other algorithms.This review aims to inspire advanced ideas and research on MPPT algorithms for hybrid PV-TEG systems.关键词
光伏/温差发电/混合光伏-温差/最大功率点跟踪/部分遮蔽条件Key words
Photovoltaic/Thermoelectric generator/Hybrid PV-TEG/MPPT/Partial shading condition引用本文复制引用
杨博,谢蕊,段金航,王景博..混合光伏-温差系统 最大功率点跟踪技术最新综述:建模、方法和前景展望[J].全球能源互联网（英文）,2023,6(5):567-591,25.基金项目
This work was supported by National Natural Science Foundation of China(61963020,62263014)and Yunnan Provincial Basic Research Project(202201AT070857). （61963020,62263014）
