{"title":"Photovoltaic Dust Soiling Statistical Representation in Doha, Qatar","authors":"N. Barth, S. Aly, S. Ahzi, B. Figgis","doi":"10.1109/IRSEC48032.2019.9078325","DOIUrl":null,"url":null,"abstract":"Qatar' ‘s and the Gulf region's photovoltaic (PV) energy potential is very high. Still, there are tradeoffs under such tropical arid climate, particularly regarding dust soiling losses during the long dry season. In-field performance analyses of PVs under varying soiling states enable the quantification of dust soiling losses. Such estimate of the soiling losses is done a posteriori, using temperature-corrected performance ratios. In the current paper, we study how exceptional events such as sandstorms and rainfalls are identified using statistical analyses of the soiling losses rates. The aim is to generate sets of synthetic years describing the regular dust soiling rates, as well as the exceptionally observed meteorological events. The proposed sets of yearlong synthetic soiling conditions have identical average statistical representativeness as our ongoing in-field experimental measurements. This especially allows economic assessments such as the optimization of dust cleaning scenarios of PV projects.","PeriodicalId":6671,"journal":{"name":"2019 7th International Renewable and Sustainable Energy Conference (IRSEC)","volume":"159 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 7th International Renewable and Sustainable Energy Conference (IRSEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRSEC48032.2019.9078325","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
Qatar' ‘s and the Gulf region's photovoltaic (PV) energy potential is very high. Still, there are tradeoffs under such tropical arid climate, particularly regarding dust soiling losses during the long dry season. In-field performance analyses of PVs under varying soiling states enable the quantification of dust soiling losses. Such estimate of the soiling losses is done a posteriori, using temperature-corrected performance ratios. In the current paper, we study how exceptional events such as sandstorms and rainfalls are identified using statistical analyses of the soiling losses rates. The aim is to generate sets of synthetic years describing the regular dust soiling rates, as well as the exceptionally observed meteorological events. The proposed sets of yearlong synthetic soiling conditions have identical average statistical representativeness as our ongoing in-field experimental measurements. This especially allows economic assessments such as the optimization of dust cleaning scenarios of PV projects.