P. Faggian, G. Decimi, E. Ciapessoni, F. Marzullo, Francesca Scavo
{"title":"未来的预测和返回水平的湿雪负荷架空线路和大雪","authors":"P. Faggian, G. Decimi, E. Ciapessoni, F. Marzullo, Francesca Scavo","doi":"10.23919/AEIT53387.2021.9626887","DOIUrl":null,"url":null,"abstract":"Wet-snow conditions trigger the formation of ice sleeves on overhead power lines and promote the occurrence of heavy snowfalls whose effects may cause serious infrastructural damages and, consequently, prolonged disruptions on the National Transmission Grid. To develop action plans aimed to strength the resilience of the Power Network, probability maps about the expected occurrences of these phenomena are required. Such maps have been elaborated by processing the outputs of 11 high-resolution Euro-CORDEX models (spatial resolution ~12km), assuming a \"Business-As-Usual scenario\" (RCP8.5). The MERIDA meteorological reanalysis dataset (spatial resolution 7 km), spanning the period 1986-2019, was used to apply the \"Equidistant Quantile Mapping\", to \"bias-correct\" model data. MERIDA was also used to develop two numerical codes: the first is a modified formulation of the \"Makkonen model\" to describe the growth of the ice-sleeve on high-voltage lines; the second is a simple \"Snow model\" to estimate the weight of the snow on the ground.After validating the codes by analyzing the results with some observations, the codes have been applied to climate models’ outputs to evaluate these phenomena until 2060 and to deduce future scenarios. Probability maps have been elaborated by means of the \"Generalized Extreme Values\" (GEV) statistical technique, used to describe the expected values at the timeframes 2020, 2030, 2040 and 2050. The results point out that such phenomena will generally decrease as snowfall will turn in rainfall due to global warming. However, if the ice-sleeve loads are likely to reduce at low-medium altitudes, these events may intensify over the highest Alpine regions as, in a warmer climate, temperatures between -1.5 and +2 ° C will be more likely thus allowing the occurrence of wet snow events at those altitudes so far spared due to their typical cold temperatures.","PeriodicalId":138886,"journal":{"name":"2021 AEIT International Annual Conference (AEIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Future projections and return levels of wet-snow load on overhead lines and heavy snowfalls\",\"authors\":\"P. Faggian, G. Decimi, E. Ciapessoni, F. Marzullo, Francesca Scavo\",\"doi\":\"10.23919/AEIT53387.2021.9626887\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wet-snow conditions trigger the formation of ice sleeves on overhead power lines and promote the occurrence of heavy snowfalls whose effects may cause serious infrastructural damages and, consequently, prolonged disruptions on the National Transmission Grid. To develop action plans aimed to strength the resilience of the Power Network, probability maps about the expected occurrences of these phenomena are required. Such maps have been elaborated by processing the outputs of 11 high-resolution Euro-CORDEX models (spatial resolution ~12km), assuming a \\\"Business-As-Usual scenario\\\" (RCP8.5). The MERIDA meteorological reanalysis dataset (spatial resolution 7 km), spanning the period 1986-2019, was used to apply the \\\"Equidistant Quantile Mapping\\\", to \\\"bias-correct\\\" model data. MERIDA was also used to develop two numerical codes: the first is a modified formulation of the \\\"Makkonen model\\\" to describe the growth of the ice-sleeve on high-voltage lines; the second is a simple \\\"Snow model\\\" to estimate the weight of the snow on the ground.After validating the codes by analyzing the results with some observations, the codes have been applied to climate models’ outputs to evaluate these phenomena until 2060 and to deduce future scenarios. Probability maps have been elaborated by means of the \\\"Generalized Extreme Values\\\" (GEV) statistical technique, used to describe the expected values at the timeframes 2020, 2030, 2040 and 2050. The results point out that such phenomena will generally decrease as snowfall will turn in rainfall due to global warming. 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Future projections and return levels of wet-snow load on overhead lines and heavy snowfalls
Wet-snow conditions trigger the formation of ice sleeves on overhead power lines and promote the occurrence of heavy snowfalls whose effects may cause serious infrastructural damages and, consequently, prolonged disruptions on the National Transmission Grid. To develop action plans aimed to strength the resilience of the Power Network, probability maps about the expected occurrences of these phenomena are required. Such maps have been elaborated by processing the outputs of 11 high-resolution Euro-CORDEX models (spatial resolution ~12km), assuming a "Business-As-Usual scenario" (RCP8.5). The MERIDA meteorological reanalysis dataset (spatial resolution 7 km), spanning the period 1986-2019, was used to apply the "Equidistant Quantile Mapping", to "bias-correct" model data. MERIDA was also used to develop two numerical codes: the first is a modified formulation of the "Makkonen model" to describe the growth of the ice-sleeve on high-voltage lines; the second is a simple "Snow model" to estimate the weight of the snow on the ground.After validating the codes by analyzing the results with some observations, the codes have been applied to climate models’ outputs to evaluate these phenomena until 2060 and to deduce future scenarios. Probability maps have been elaborated by means of the "Generalized Extreme Values" (GEV) statistical technique, used to describe the expected values at the timeframes 2020, 2030, 2040 and 2050. The results point out that such phenomena will generally decrease as snowfall will turn in rainfall due to global warming. However, if the ice-sleeve loads are likely to reduce at low-medium altitudes, these events may intensify over the highest Alpine regions as, in a warmer climate, temperatures between -1.5 and +2 ° C will be more likely thus allowing the occurrence of wet snow events at those altitudes so far spared due to their typical cold temperatures.