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e4clim 1.0 : The Energy for CLimate Integrated Model: Description and Application to Italy

Abstract : We develop an open-source Python software integrating flexibility needs from Variable Renewable Energies (VREs) in the development of regional energy mixes. It provides a flexible and extensible tool to researchers/engineers, and for education/outreach. It aims at evaluating and optimizing energy deployment strategies with high shares of VRE; assessing the impact of new technologies and of climate variability; conducting sensitivity studies. Specifically, to limit the algorithm’s complexity, we avoid solving a full-mix cost-minimization problem by taking the mean and variance of the renewable production-demand ratio as proxies to balance services. Second, observations of VRE technologies being typically too short or nonexistent, the hourly demand and production are estimated from climate time-series and fitted to available observations. We illustrate e4clim’s potential with an optimal recommissioning-study of the 2015 Italian PV-wind mix testing different climate-data sources and strategies and assessing the impact of climate variability and the robustness of the results.
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Soumis le : jeudi 14 novembre 2019 - 08:57:53
Dernière modification le : mardi 8 décembre 2020 - 03:43:50


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Alexis Tantet, Marc Stéfanon, Philippe Drobinski, Jordi Badosa, Silvia Concettini, et al.. e4clim 1.0 : The Energy for CLimate Integrated Model: Description and Application to Italy. Energies, MDPI, 2019, 12 (22), pp.4299. ⟨10.3390/en12224299⟩. ⟨hal-01962044v4⟩



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