110 citations · 215 across the 13 of their papers we have counts for
13 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 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…
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…
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…
Creating synthetic energy meter data using conditional diffusion and building metadata
Chun Fu, Hussain Kazmi, Matias Quintana +1
Advances in machine learning and increased computational power have driven progress in energy-related research. However, limited access to private energy data from buildings hinder…
The Forecastability of Underlying Building Electricity Demand from Time Series Data
Mohamad Khalil, A. Stephen McGough, Hussain Kazmi +1
Forecasting building energy consumption has become a promising solution in Building Energy Management Systems for energy saving and optimization. Furthermore, it can play an import…
The Building Data Genome Directory -- An open, comprehensive data sharing platform for building performance research
Xiaoyu Jin, Chun Fu, Hussain Kazmi +6
The building sector plays a crucial role in the worldwide decarbonization effort, accounting for significant portions of energy consumption and environmental effects. However, the…
On the contribution of pre-trained models to accuracy and utility in modeling distributed energy resources
Hussain Kazmi, Pierre Pinson
Despite their growing popularity, data-driven models of real-world dynamical systems require lots of data. However, due to sensing limitations as well as privacy concerns, this dat…
Is your forecaster smarter than an energy engineer: a deep dive into electricity price forecasting
Maria Margarida Mascarenhas, Hussain Kazmi
The field of electricity price forecasting has seen significant advances in the last years, including the development of new, more accurate forecast models. These models leverage s…
Deep Reinforcement Learning for Optimal Control of Space Heating
Adam Nagy, Hussain Kazmi, Farah Cheaib +1
Classical methods to control heating systems are often marred by suboptimal performance, inability to adapt to dynamic conditions and unreasonable assumptions e.g. existence of bui…
Valuing knowledge, information and agency in Multi-agent Reinforcement Learning: a case study in smart buildings
Hussain Kazmi, Johan Suykens, Johan Driesen
Increasing energy efficiency in buildings can reduce costs and emissions substantially. Historically, this has been treated as a local, or single-agent, optimization problem. Howev…
Deep Reinforcement Learning based Optimal Control of Hot Water Systems
Hussain Kazmi, Fahad Mehmood, Stefan Lodeweyckx +1
Energy consumption for hot water production is a major draw in high efficiency buildings. Optimizing this has typically been approached from a thermodynamics perspective, decoupled…