155 citations · 356 across the 34 of their papers we have counts for
10 papers · 1 filter
Spatio-temporal modelling of electric vehicle charging demand
Kaoutar Bouaachra, Yvenn Amara-Ouali, Yannig Goude +1
Accurate forecasting of electric vehicle (EV) charging demand is critical for grid management and infrastructure planning. Yet the field continues to rely on legacy benchmarks; suc…
Generative Unsupervised Downscaling of Climate Models via Domain Alignment: Application to Wind Fields
Julie Keisler, Boutheina Oueslati, Anastase Charantonis +2
General Circulation Models (GCMs) are widely used for future climate projections, but their coarse spatial resolution and systematic biases limit their direct use for impact studie…
Adaptive probabilistic forecasting of French electricity spot prices
Grégoire Dutot, Margaux Zaffran, Olivier Féron +1
Electricity price forecasting (EPF) plays a major role for electricity companies as a fundamental entry for trading decisions or energy management operations. As electricity can no…
Human spatial dynamics for electricity demand forecasting: the case of France during the 2022 energy crisis
Nathan Doumèche, Yann Allioux, Yannig Goude +1
Accurate electricity demand forecasting is crucial to meet energy security and efficiency, especially when relying on intermittent renewable energy sources. Recently, massive savin…
Adaptive Probabilistic Forecasting of Electricity (Net-)Load
Joseph de Vilmarest, Jethro Browell, Matteo Fasiolo +2
Electricity load forecasting is a necessary capability for power system operators and electricity market participants. The proliferation of local generation, demand response, and e…
Hierarchical transfer learning with applications for electricity load forecasting
Anestis Antoniadis, Solenne Gaucher, Yannig Goude
The recent abundance of data on electricity consumption at different scales opens new challenges and highlights the need for new techniques to leverage information present at finer…
State-Space Models Win the IEEE DataPort Competition on Post-covid Day-ahead Electricity Load Forecasting
Joseph de Vilmarest, Yannig Goude
We present the winning strategy of an electricity demand forecasting competition. This competition was organized to design new forecasting methods for unstable periods such as the…
Adaptive Methods for Short-Term Electricity Load Forecasting During COVID-19 Lockdown in France
David Obst, Joseph de Vilmarest, Yannig Goude
The coronavirus disease 2019 (COVID-19) pandemic has urged many governments in the world to enforce a strict lockdown where all nonessential businesses are closed and citizens are…
Additive stacking for disaggregate electricity demand forecasting
Christian Capezza, Biagio Palumbo, Yannig Goude +2
Future grid management systems will coordinate distributed production and storage resources to manage, in a cost effective fashion, the increased load and variability brought by th…
Clustering electricity consumers using high-dimensional regression mixture models
Emilie Devijver, Yannig Goude, Jean-Michel Poggi
Massive informations about individual (household, small and medium enterprise) consumption are now provided with new metering technologies and the smart grid. Two major exploitatio…