Article published in Energies
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 higher shares of VRE, assessing the impact of new technologies and of climate variability and 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.
Ce séminaire porte sur la finance solidaire et la finance à impact qui sont considérées comme des modes de financement alternatifs ou complémentaires aux circuits financiers traditionnels. Il interroge en particulier l’évolution de ces deux types de finances au regard de leurs objectifs affichés, étant donné leur essor important depuis une quinzaine d’années.
This one-day workshop brings together researchers working on the design, evaluation, and impact of climate policies aimed at fostering the development and diffusion of low-carbon technologies. The presentations will cover a range of topics including the regulation of urban transport emissions, the integration of carbon dioxide removal into energy markets, the strategic adoption of...