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

Alexis Tantet; Silvia Concettini; Claudia d'Ambrosio; Dimitri Thomopulos; Peter Tankov; Marc Stéfanon; Philippe Drobinski; Jordi Badosa; Anna Créti

arXiv · 1812.09181

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

Alexis Tantet·Silvia Concettini·Claudia d'Ambrosio·Dimitri Thomopulos·Peter Tankov·Marc Stéfanon·Philippe Drobinski·Jordi Badosa·Anna Créti

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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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Alexis Tantet, Silvia Concettini, Claudia d'Ambrosio, Dimitri Thomopulos, Peter Tankov, Marc Stéfanon, Philippe Drobinski, Jordi Badosa, Anna Créti. 2018-12-21. e4clim 1.0 : The Energy for CLimate Integrated Model: Description and Application to Italy. https://arxiv.org/abs/1812.09181

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