A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

作     者：Dazhi YANG Xiang’ao XIA Martin János MAYER Dazhi YANG;Xiang'ao XIA;Martin János MAYER

作者机构：School of Electrical Engineering and AutomationHarbin Institute of TechnologyHarbin 150001HeilongjiangChina Key Laboratory for Middle Atmosphere and Global Environment Observation(LAGEO)Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Department of Energy EngineeringFaculty of Mechanical EngineeringBudapest University of Technology and EconomicsMűegyetem rkp.3Budapest H-1111Hungary 

出 版 物：《Advances in Atmospheric Sciences》 (大气科学进展（英文版）)

年 卷 期：2024年第41卷第6期

页      面：1023-1067页

核心收录：

学科分类：080703[工学-动力机械及工程] 08[工学] 0807[工学-动力工程及工程热物理] 

基　　金：supported by the National Natural Science Foundation of China(project no.42375192),and the China Meteorological Administration Climate Change Special Program(CMA-CCSP project no.QBZ202315) supported by the National Natural Science Foundation of China(project no.42030608) supported by the National Research,Development and Innovation Fund,project no.OTKA-FK 142702 by the Hungarian Academy of Sciences through the Sustainable Development and Technologies National Programme(FFT NP FTA)and the János Bolyai Research Scholarship 

主　　题：review energy meteorology solar power curve model chain solar power prediction 

摘      要：Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly *** numerous trending topics,energy meteorology has been attracting the most attention *** essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical *** this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power *** power curves can be modeled in two primary ways,one of regression and the other of model *** classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.