2 citations · 2 across the 3 of their papers we have counts for
5 papers
Decision-focused learning for optimal PV-Battery scheduling
Joris Depoortere, Hussain Kazmi, Johan Driesen
The use of residential photovoltaics has increased dramatically in recent years. With battery systems becoming more affordable, the optimal operation of a photovoltaic-battery syst…
A review of imbalance price forecasting algorithms in Europe: algorithms, metrics and the way forward
Arnaud Verstraeten, Maria Margarida Mascarenhas, Hussain Kazmi
Renewable electricity generation has grown significantly across many European power systems, leading to a greener energy mix, but also additional complexity in balancing electricit…
Empirical evaluation of Time Series Foundation Models for Day-ahead and Imbalance Electricity Price Forecasting in Belgium
Chi Bui, Maria Margarida Mascarenhas, Arnaud Verstraeten +1
Recent advances in Time Series Foundation Models (TSFMs) promise zero-shot forecasting capabilities with minimal task-specific training. While these models have shown strong perfor…
SolNet: Open-source deep learning models for photovoltaic power forecasting across the globe
Joris Depoortere, Johan Driesen, Johan Suykens +1
Deep learning models have gained increasing prominence in recent years in the field of solar pho-tovoltaic (PV) forecasting. One drawback of these models is that they require a lot…
Leveraging Asynchronous Cross-border Market Data for Improved Day-Ahead Electricity Price Forecasting in European Markets
Maria Margarida Mascarenhas, Jilles De Blauwe, Mikael Amelin +1
Accurate short-term electricity price forecasting is crucial for strategically scheduling demand and generation bids in day-ahead markets. While data-driven techniques have shown c…