{"title":"A Review of Applications of Probability Distribution Functions in Assessment of Solar Resource Potential","authors":"Lehlohonolo Mojaki, N. Mbuli","doi":"10.1109/PSET56192.2022.10100605","DOIUrl":null,"url":null,"abstract":"This publication presents the results of a review of publications on the applications and use of probability distribution functions (pdfs) in assessing potential for solar energy, based on the irradiance data for areas considered for harvesting solar energy. The literature search was done using Google Scholar, most relevant publications were selected and reviewed. A total of 15 publications, in which 13 pdfs were utilized, were selected for the review. In this publication, the authors identified the pdfs that have been used in assessing solar resource potential. Furthermore, these pdfs were analyzed in terms of their frequency of use, and also on the basis in which a particular pdfwas nominated the best performing pdf in the studies. This paper provides a resource to researchers interested in the subject of renewable energy, in general, and the use of pdfs to assess solar resource potential, in particular.","PeriodicalId":402897,"journal":{"name":"2022 IEEE International Conference on Power Systems and Electrical Technology (PSET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Power Systems and Electrical Technology (PSET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PSET56192.2022.10100605","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This publication presents the results of a review of publications on the applications and use of probability distribution functions (pdfs) in assessing potential for solar energy, based on the irradiance data for areas considered for harvesting solar energy. The literature search was done using Google Scholar, most relevant publications were selected and reviewed. A total of 15 publications, in which 13 pdfs were utilized, were selected for the review. In this publication, the authors identified the pdfs that have been used in assessing solar resource potential. Furthermore, these pdfs were analyzed in terms of their frequency of use, and also on the basis in which a particular pdfwas nominated the best performing pdf in the studies. This paper provides a resource to researchers interested in the subject of renewable energy, in general, and the use of pdfs to assess solar resource potential, in particular.