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Energies | Environnement
Nos Working papers
Fast electrification of the energy system and end-uses, either direct or indirect, is a cornerstone of the transition to carbon neutrality. Building an ensemble of 704 scenarios to 2050, we analyze how carbon price, technological and resource assumptions impact the arbitrage between direct and indirect electrification. Using novel explainability methods from machine learning, we attribute changes in electrification rates either to the individual or combined effects of model assumptions, or features. Total electrification is mostly driven by direct electric uses; individual effects explain up to 80% of it. Conversely, the development of indirect electrification, through hydrogen and e-fuels, is conditional on complex interaction effects between features, whose magnitude can reach up to three times the net effect in the transport sector. Moreover, we measure how interaction patterns between features reconfigure when carbon price increases. By explaining transition scenarios, our study provides sound evidence in favor of coordinated transition policy bundles.
This paper aims to study the intraday dynamics in the unique context of the French balancing phase. Through econometric modelling, we assess how traded volume, price level, and price volatility are influenced by balancing adjustment needs and short-term flexibility availability. In particular, the role of forecast error from renewables production located in France or abroad is assessed. Building on the methodology of Soysal et al. (2017) in combination with panel econometric methods, we can disentangle the effect on market dynamics of positive and negative forecast error.
This article proposes a method for calculating the probability of a (potentially non-linear) combination of random events, and finds numerous applications in the study of energy systems under uncertainty. For example, it allows the calculation of the probability distribution of metrics associated with the stability of the electrical system (LOLP, amount of electricity not supplied to end users), the aggregate production of a set of solar and wind power generation units taking into account correlations between sites, or the probability distribution of curtailment for a renewable electricity producer.
The paper introduces a multi-regional, multi-commodity investment and operational optimization model to evaluate the levelised transportation cost of hydrogen and its derivatives for specific maritime trade routes. It is formulated as a Mixed-Integer Linear Programming (MILP) with both annual investment and daily operational decisions, covering conversion, export terminal storage, transportation, import terminal storage and reconversion flows. Our model both accounts for stock and flow constraints, and includes factors influencing transportation costs such as maritime distance, port charges and canal fees, ship size and required power, fuel consumption and boil-off gas (BOG) losses.
Cette étude réalisée par le CEA I-Tésé s'intéresse à la structuration des besoins de chaleur du secteur industriel actuels et futurs. La compréhension fine des besoins sectoriels représente un enjeu crucial pour l'élaboration de stratégies de décarbonation efficaces. Les besoins en chaleur industrielle présentent en effet une forte hétérogénéité, marquée par une forte dimension locale et l'utilisation de niveaux de température variés. De plus, les évolutions futures de l'appareil production français et le potentiel d'électrification d'une partie des procédés auront un impact sur les besoins en chaleur futur.
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Acteur majeur de la recherche, du développement et de l'innovation, le CEA intervient dans quatre grands domaines : énergies bas carbone, défense et sécurité, technologies pour l’information et technologies pour la santé.