Zobrazeno 1 - 10
of 202
pro vyhledávání: '"Messagie, Maarten"'
Autor:
Ruddick, Julian, Ceusters, Glenn, Van Kriekinge, Gilles, Genov, Evgenii, Coosemans, Thierry, Messagie, Maarten
Recent advancements in machine learning based energy management approaches, specifically reinforcement learning with a safety layer (OptLayerPolicy) and a metaheuristic algorithm generating a decision tree control policy (TreeC), have shown promise.
Externí odkaz:
http://arxiv.org/abs/2408.07435
Autor:
Genov, Evgenii, Ruddick, Julian, Bergmeir, Christoph, Vafaeipour, Majid, Coosemans, Thierry, Garcia, Salvador, Messagie, Maarten
This research addresses the challenge of integrating forecasting and optimization in energy management systems, focusing on the impacts of switching costs, forecast accuracy, and stability. It proposes a novel framework for analyzing online optimizat
Externí odkaz:
http://arxiv.org/abs/2407.03368
Safe reinforcement learning (RL) with hard constraint guarantees is a promising optimal control direction for multi-energy management systems. It only requires the environment-specific constraint functions itself a priori and not a complete model. Th
Externí odkaz:
http://arxiv.org/abs/2304.08897
Autor:
Ruddick, Julian, Camargo, Luis Ramirez, Putratama, Muhammad Andy, Messagie, Maarten, Coosemans, Thierry
Energy management systems (EMS) have classically been implemented based on rule-based control (RBC) and model predictive control (MPC) methods. Recent research are investigating reinforcement learning (RL) as a new promising approach. This paper intr
Externí odkaz:
http://arxiv.org/abs/2304.08310
Reinforcement learning (RL) is a promising optimal control technique for multi-energy management systems. It does not require a model a priori - reducing the upfront and ongoing project-specific engineering effort and is capable of learning better re
Externí odkaz:
http://arxiv.org/abs/2207.03830
Autor:
Ruddick, Julian, Genov, Evgenii, Camargo, Luis Ramirez, Coosemans, Thierry, Messagie, Maarten
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-dimensional time series forecast and a novel approach to large-scale opti
Externí odkaz:
http://arxiv.org/abs/2202.12595
Autor:
Felice, Alex, Rakocevic, Lucija, Peters, Leen, Messagie, Maarten, Coosemans, Thierry, Camargo, Luis Ramirez
Renewable energy communities (RECs) are prominent initiatives to provide end consumers an active role in the energy sector, raise awareness on the importance of renewable energy (RE) technologies and increase their share in the energy system thus red
Externí odkaz:
http://arxiv.org/abs/2202.05151
Autor:
Goncearuc, Andrei, De Cauwer, Cedric, Sapountzoglou, Nikolaos, Kriekinge, Gilles Van, Huber, Dominik, Messagie, Maarten, Coosemans, Thierry
Publikováno v:
In Energy Reports December 2024 12:27-41
Autor:
van den Oever, Anne E.M., Puricelli, Stefano, Costa, Daniele, Thonemann, Nils, Lavigne Philippot, Maeva, Messagie, Maarten
Publikováno v:
In Cleaner Environmental Systems June 2024 13
Autor:
Ceusters, Glenn, Rodríguez, Román Cantú, García, Alberte Bouso, Franke, Rüdiger, Deconinck, Geert, Helsen, Lieve, Nowé, Ann, Messagie, Maarten, Camargo, Luis Ramirez
Model-predictive-control (MPC) offers an optimal control technique to establish and ensure that the total operation cost of multi-energy systems remains at a minimum while fulfilling all system constraints. However, this method presumes an adequate m
Externí odkaz:
http://arxiv.org/abs/2104.09785