A Climatological Survey of Corsica for Power System Analyses

Claudio Francesco Nicolosi, Giuseppe Marco Tina, Ghjuvan Antone Faggianelli and Gilles Notton ()
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Claudio Francesco Nicolosi: Department of Electrical, Electronic and Computer Engineering (DIEEI), University of Catania, Viale Andrea Doria n.6, 95125 Catania, Italy
Giuseppe Marco Tina: Department of Electrical, Electronic and Computer Engineering (DIEEI), University of Catania, Viale Andrea Doria n.6, 95125 Catania, Italy
Ghjuvan Antone Faggianelli: Science for Environment Laboratory, University of Corsica, UMR CNRS 6134, 20000 Ajaccio, France
Gilles Notton: Science for Environment Laboratory, University of Corsica, UMR CNRS 6134, 20000 Ajaccio, France

Sustainability, 2023, vol. 15, issue 21, 1-30

Abstract: Climate and climate change can impact present and future energy production and demand. In light of this issue, this paper conducts climatological analyses focused on the following meteorological quantities: shortwave downward irradiance (SDI), precipitation (Pr), relative humidity (RH), air temperature ( T a ), 10 m wind speed ( v 10 ), and diurnal temperature range (DTR) for four locations in Corsica. The climate analyses of these atmospheric variables consist of three parts: (1) analysis of the historical trends; (2) correlation analysis; and (3) analysis of climate projections for the decades to come. It is observed that climate change is causing alterations in the trends of Pr, RH, T a , v 10 , and DTR. The correlation analysis reveals a positive correlation for the T a -SDI and v 10 -Pr pairs (both annually and seasonally), and a negative correlation for T a -RH (annually and in summer). For the other variable pairs, the sign of the correlations varies depending on the time period and site considered. The trends in the projections from the multi-model ensemble simulations are consistent or inconsistent with each other depending on the time period (annual or seasonal) considered. The observed historical trends suggest that medium-term planning of the Corsican electric power system should already consider ongoing climate change. The correlation analysis provides insights into the combined effect of different atmospheric variables on electrical power systems (EPSs). Climate projections suggest studying long-term planning that is a compromise among the different (but equally likely) outputs of different climate models.

Keywords: climate; climate change; correlation analysis; electricity production; energy demand; climate models; multi-model ensemble; energy meteorology (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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