The energy transition is a multidisciplinary challenge that warrants solutions that are robust and sustainable. Energy flexibility, one of the key pillars of the energy transition, is an umbrella term that covers multiple innovative solutions implemented at all levels of the electric grid to ensure power quality standards, amongst other objectives. Low-tech, on the other hand, emphasizes designing, producing, and sustainably implementing solutions. Therefore, considering the multidisciplinary nature of energy transition and the existing energy flexibility solutions, the purpose of this research work is multilateral: first, it presents the concept of low-tech and its associated mechanisms; then, it addresses the misconceptions and similarities that low-tech might have with other innovation approaches; and finally, it provides an assessment of existing flexibility solutions using low-tech as a tool. The result of this assessment is presented qualitatively and indicates that indirect energy flexibility solutions rank higher on a low-tech scale relative to supply-side energy flexibility solutions and energy storage flexibility solutions.

Electric vehicles are considered by many as an emission-free or low-emission solution to meet the challenge of sustainable transportation. However, the operational input, electrical energy, has an associated cost, greenhouse gasses, which results in indirect emissions. Given this knowledge, we pose the following question: “Are zero-emission transportation targets achievable given our current energy mix?” The objective of this article is to assess the impact of a grid’s energy mix on the indirect emissions of an electric vehicle. The study considers real-world data, vehicle usage data from an electric vehicle, and carbon intensity data for India, the USA, France, the Netherlands, Brazil, Germany, and Poland. Linear programming-based optimization is used to compute the best charging scenario for each of the given grids and, consequently, the indirect emissions are compared to those of a high-efficiency 1.5 L diesel internal combustion engine for the vehicle: a 2019 Renault Clio dCi 85. The results indicate that for grids with low renewable energy penetration, such as those of Poland and India (Maharashtra), an electric vehicle, even when optimally charged, can be classified as neither a low- nor zero-emission alternative to normal thermal vehicles. Also, for grids with elevated levels of variation in their carbon intensity, there is significant potential to reduce the carbon footprint related to charging an electric vehicle. This article provides a real-world perspective of how an electric vehicle performs in the face of different energy mixes and serves as a precursor to the development of robust indicators for determining the carbon reductions related to the e-mobility transition.

Un cycle de vie des données ouvertes pour la transition énergétique : organisation, méthodes et outils: Les données ouvertes sont reconnues comme un facteur clé de la transition socio-écologique et énergétique, car elles peuvent favoriser la sobriété, la flexibilité et l'innovation. Leur impact se traduit par une accélération de la numérisation des systèmes énergétiques et par la promotion de la création de connaissances dans le secteur de l'énergie. Cependant, malgré ces avantages, la science ouverte – en particulier les données ouvertes – n'occupe pas encore une place centrale dans les domaines de l'énergie et du génie électrique. Pour combler cette lacune, cette thèse présente Open Energy Data Lifecycle (OpEnDaLe), une méthodologie qui guide le cycle de vie complet des ensembles de données énergétiques ouvertes, depuis leur création jusqu'aux boucles d'interaction/rétroaction nécessaires après leur réutilisation éventuelle. L'objectif est d'accroître la disponibilité et la réutilisation des ensembles de données énergétiques en proposant des outils et des méthodes spécifiques pour les différentes étapes du cycle de vie des données, en mettant l'accent sur le suivi de l'utilisation et de l'impact, ainsi que sur la facilitation de l'interaction avec les utilisateurs des données. Cette méthodologie est ensuite appliquée à cinq études de cas de l'Observatoire de Transition Énergétique, un programme d'observation universitaire de l'Université Grenoble Alpes, afin de présenter les différentes étapes du cycle de vie. Ces études de cas mettront en évidence la manière dont la nature des données influence le cycle de vie. Plusieurs outils, notamment un tableau de bord de suivi et un forum en ligne, sont également utilisés pour mettre en évidence les étapes nécessaires du cycle de vie. Au-delà des études de cas, cette thèse démontre les avantages d'une approche axée sur le cycle de vie, plutôt que sur un partage ponctuel et ad hoc, pour exploiter pleinement la valeur des ensembles de données énergétiques. Elle souligne également l'importance des espaces d'interaction communautaires tels que le forum OTE en tant que centres d'échange de connaissances, en attendant l'émergence de normes universelles en matière de métadonnées dans le domaine de l'énergie.

This data paper presents the dataset from a study on the use of electric vehicles (EVs). This dataset covers the first dataset collected in this study: the usage data from a Renault Zoe over 3 years. The process of collection of the dataset, its treatment, and descriptions of all the included variables are detailed. The collection of this dataset represents an iteration of participative research in the personal mobility domain as the dataset was collected with low-cost commercially available equipment and open-source software. Some of the challenges of providing the dataset are also discussed: the most pertinent being the intermittent nature of data collection as an android phone and OBDII adapter were used to collect the dataset.

This data paper presents the dataset from a study on the use of electric vehicles (EVs). This dataset covers the first dataset collected in this study: the usage data from a Renault Zoe over 3 years. The process of collection of the dataset, its treatment, and descriptions of all the included variables are detailed. The collection of this dataset represents an iteration of participative research in the personal mobility domain as the dataset was collected with low-cost commercially available equipment and open-source software. Some of the challenges of providing the dataset are also discussed: the most pertinent being the intermittent nature of data collection as an android phone and OBDII adapter were used to collect the dataset.