Spatial projections of solar PV installations at subnational level: Accuracy testing of regression models

Article Article scientifique Article Spatial projections of solar PV installations at subnational level: Accuracy testing of regression models eng 2020 author Muller Jonas 931161 author Trutnevyte Evelina 0000-0002-1716-6192 892077 114747 10.1016/j.apenergy.2020.114747 0306-2619 https://linkinghub.elsevier.com/retrieve/pii/S0306261920302592 As the growth of solar photovoltaics (PV) accelerates, spatial PV projections at subnational level are necessary for planning grid infrastructure and addressing demand-supply balancing challenges, posed by this intermittent source of electricity. Although spatial models of weather-dependent PV productivity are common, few studies have focused on projections of PV installations. This study uses a comprehensive dataset with 68′341 PV installations in Switzerland to develop 1- to 5-year-ahead projections of PV installations at a level of 143 Swiss districts. A new modelling methodology is demonstrated, using in-sample and out-of-sample accuracy testing of a multiple linear and two spatial regression models with techno-economic and socio-demographic predictor variables. The results show that exploitable solar PV potential, household size, population density, and electricity prices are predictors with positive effect, and the share of unproductive land area is a predictor of PV installations at a district level with negative effect. Spatial regression models point to the importance of spatial spillovers across proximate districts. The accuracy testing shows that spatial regression models have slightly higher accuracy during in-sample testing of projections, but concerning out-of-sample testing, the multiple linear regression model performs equally well for 1- to 5-year-ahead projections. Solar PV Spatial projections Technology diffusion Spatial energy models Model accuracy Out-of-sample testing Dewey 333.7-333.9 Dewey 550 18 Institut des sciences de l'environnement 0DB 41 Département F.-A. Forel des sciences de l'environnement et de l'eau 153 false 1245 FORE10 Renewable Energy Systems 945 ISE Energie 938 ISE Pôle Sciences Applied Energy 265 20fa7852-0847-4a72-8ca5-bcfe614840d8 Article (Accepted version) Public Mueller_and_Trutnevyte_2020_DOCversion.pdf 2505747 application/pdf Restricted 2021-04-02 openAccess Centres et instituts / Institut des sciences de l'environnement Faculté des sciences / Section des sciences de la Terre et de l'Environnement / Département F.-A. Forel des sciences de l'environnement et de l'eau

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Spatial projections of solar PV installations at subnational level: Accuracy testing of regression models	Applied Energy			2020	586	373

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Muller, Jonas