Deep learning-based multivariate probabilistic forecasting for short-term scheduling in power markets
JF Toubeau, J Bottieau, F Vallée… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
In the current competition framework governing the electricity sector, complex dependencies
exist between electrical and market data, which complicates the decision-making procedure …
exist between electrical and market data, which complicates the decision-making procedure …
Data-driven scheduling of energy storage in day-ahead energy and reserve markets with probabilistic guarantees on real-time delivery
Energy storage systems (ESS) may provide the required flexibility to cost-effectively
integrate weather-dependent renewable generation, in particular by offering operating …
integrate weather-dependent renewable generation, in particular by offering operating …
Very-short-term probabilistic forecasting for a risk-aware participation in the single price imbalance settlement
J Bottieau, L Hubert, Z De Grève… - … on Power Systems, 2019 - ieeexplore.ieee.org
The single imbalance pricing is an emerging mechanism in European electricity markets
where all positive and negative imbalances are settled at a unique price. This real-time …
where all positive and negative imbalances are settled at a unique price. This real-time …
[HTML][HTML] A novel day-ahead regional and probabilistic wind power forecasting framework using deep CNNs and conformalized regression forests
Regional forecasting is crucial for a balanced energy delivery system and for achieving the
global transition to clean energy. However, regional wind forecasting is challenging due to …
global transition to clean energy. However, regional wind forecasting is challenging due to …
Capturing spatio-temporal dependencies in the probabilistic forecasting of distribution locational marginal prices
This article presents a new spatio-temporal framework for the day-ahead probabilistic
forecasting of Distribution Locational Marginal Prices (DLMPs). The approach relies on a …
forecasting of Distribution Locational Marginal Prices (DLMPs). The approach relies on a …
Machine learning techniques for improving self-consumption in renewable energy communities
Renewable Energy Communities consist in an emerging decentralized market mechanism
which allows local energy exchanges between end-users, bypassing the traditional …
which allows local energy exchanges between end-users, bypassing the traditional …
Recalibration of recurrent neural networks for short-term wind power forecasting
JF Toubeau, PD Dapoz, J Bottieau, A Wautier… - Electric Power Systems …, 2021 - Elsevier
This paper is focused on the day-ahead prediction of the onshore wind generation. This
information is indeed published each day, ahead of the market clearing, by European …
information is indeed published each day, ahead of the market clearing, by European …
Chance-constrained scheduling of underground pumped hydro energy storage in presence of model uncertainties
Abandoned underground quarries or mines may be rehabilitated as natural reservoirs for
underground pumped hydro energy storage (UPHES). In addition to the inherent modeling …
underground pumped hydro energy storage (UPHES). In addition to the inherent modeling …
Forecast-driven stochastic scheduling of a virtual power plant in energy and reserve markets
JF Toubeau, TH Nguyen, H Khaloie… - IEEE Systems …, 2021 - ieeexplore.ieee.org
Virtual power plants (VPPs) offer a cost-effective solution to incentivize coordination
between different resources participating in joint energy and reserve markets. However …
between different resources participating in joint energy and reserve markets. However …
Non‐linear hybrid approach for the scheduling of merchant underground pumped hydro energy storage
JF Toubeau, S Iassinovski, E Jean… - IET Generation …, 2019 - Wiley Online Library
As a result of the increased penetration of stochastic renewable generation, power systems
have a growing need of flexibility for compensating real‐time mismatches between …
have a growing need of flexibility for compensating real‐time mismatches between …