P. Faggian, Arianna Trevisiol, E. Ciapessoni, F. Marzullo, Francesca Scavo
{"title":"Future projections of wet-snow events and loads on overhead lines","authors":"P. Faggian, Arianna Trevisiol, E. Ciapessoni, F. Marzullo, Francesca Scavo","doi":"10.23919/AEIT56783.2022.9951854","DOIUrl":null,"url":null,"abstract":"Heavy snowfalls may have serious effects on National Transmission and Distribution Grids because they trigger the formation of sleeves on overhead power lines whose loads may cause outages and, consequently, prolonged disruptions of the energy supply. Some future projections have been elaborated on the basis of 12 high-resolution Euro-CORDEX models (spatial resolution of ~12km) under the configurations RCP8.5 (\"Business-As-Usual\" scenario) and RCP4.5 (scenario with moderate reductions of greenhouse gases emission) to provide information for planning actions to strength the resilience of the Power Network. Moreover, the meteorological reanalysis dataset MERIDA (with 4km spatial resolution, covering the period 1990-2020) was used for: i) implementing as well as validating the \"Makkonen model\" to describe the growth of the wet-snow sleeve on high-voltage lines; ii) applying a \"bias-correction\" of the climate data through the \"Equidistant Quantile Mapping\" technique; iii) elaborating the reference scenarios 2001-2020 about wet-snow occurrences and wet-snow sleeve loads. After comparing the results with some observations and the reference scenarios, climate models’ outputs have been used to evaluate the future projections in the periods 2021-2040, 2031-2050, 2041-2060. Referring to Extreme Value Analysis, probability maps have been elaborated by means of the \"Generalized Extreme Values\" distributions. The results point out that wet-snow phenomena will generally decrease as snowfall will turn in rainfall due to global warming. Instead, these events may intensify over the highest Alpine regions as temperatures will be more likely in the range of wet-snow conditions in a future warmer climate.","PeriodicalId":253384,"journal":{"name":"2022 AEIT International Annual Conference (AEIT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 AEIT International Annual Conference (AEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/AEIT56783.2022.9951854","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Heavy snowfalls may have serious effects on National Transmission and Distribution Grids because they trigger the formation of sleeves on overhead power lines whose loads may cause outages and, consequently, prolonged disruptions of the energy supply. Some future projections have been elaborated on the basis of 12 high-resolution Euro-CORDEX models (spatial resolution of ~12km) under the configurations RCP8.5 ("Business-As-Usual" scenario) and RCP4.5 (scenario with moderate reductions of greenhouse gases emission) to provide information for planning actions to strength the resilience of the Power Network. Moreover, the meteorological reanalysis dataset MERIDA (with 4km spatial resolution, covering the period 1990-2020) was used for: i) implementing as well as validating the "Makkonen model" to describe the growth of the wet-snow sleeve on high-voltage lines; ii) applying a "bias-correction" of the climate data through the "Equidistant Quantile Mapping" technique; iii) elaborating the reference scenarios 2001-2020 about wet-snow occurrences and wet-snow sleeve loads. After comparing the results with some observations and the reference scenarios, climate models’ outputs have been used to evaluate the future projections in the periods 2021-2040, 2031-2050, 2041-2060. Referring to Extreme Value Analysis, probability maps have been elaborated by means of the "Generalized Extreme Values" distributions. The results point out that wet-snow phenomena will generally decrease as snowfall will turn in rainfall due to global warming. Instead, these events may intensify over the highest Alpine regions as temperatures will be more likely in the range of wet-snow conditions in a future warmer climate.