28 citations · 38 across the 4 of their papers we have counts for
4 papers
Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems
Julian Ruddick, Glenn Ceusters, Gilles Van Kriekinge +4
Recent advancements in machine learning based energy management approaches, specifically reinforcement learning with a safety layer (OptLayerPolicy) and a metaheuristic algorithm g…
Balancing Forecast Accuracy and Switching Costs in Online Optimization of Energy Management Systems
Evgenii Genov, Julian Ruddick, Christoph Bergmeir +4
This study investigates the integration of forecasting and optimization in energy management systems, with a focus on the role of switching costs -- penalties incurred from frequen…
Predict+Optimize Problem in Renewable Energy Scheduling
Christoph Bergmeir, Frits de Nijs, Evgenii Genov +25
Predict+Optimize frameworks integrate forecasting and optimization to address real-world challenges such as renewable energy scheduling, where variability and uncertainty are criti…
Evolutionary scheduling of university activities based on consumption forecasts to minimise electricity costs
Julian Ruddick, Evgenii Genov, Luis Ramirez Camargo +2
This paper presents a solution to a predict then optimise problem which goal is to reduce the electricity cost of a university campus. The proposed methodology combines a multi-dim…