3 papers
eess.SY2025
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…
eess.SY2024
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…
cs.LG2024
TreeC: a method to generate interpretable energy management systems using a metaheuristic algorithm
Julian Ruddick, Luis Ramirez Camargo, Muhammad Andy Putratama +2
Energy management systems (EMS) have traditionally been implemented using rule-based control (RBC) and model predictive control (MPC) methods. However, recent research has explored…