Simulation-Based Evaluation and Optimization of Control Strategies in Buildings
2018
Research leading to these results has been partially supported by the Modelling Optimization of Energy
Efficiency in Buildings for Urban Sustainability (MOEEBIUS) project. This project has received funding from
the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 680517.
Georgios Giannakis and Dimitrios Rovas gratefully acknowledge financial support from the European Commission
H2020-EeB5-2015 project “Optimised Energy Efficient Design Platform for Refurbishment at District Level” under
Contract #680676 (OptEEmAL). Georgios Kontes and Christopher Mutschler gratefully acknowledge financial
support from the Federal Ministry of Education and Research of Germany in the framework of Machine Learning
Forum (grant number 01IS17071). Georgios Kontes, Natalia Panagiotidou, Simone Steiger and Gunnar Gruen
gratefully acknowledge use of the services and facilities of the Energie Campus Nurnberg. The APC was funded
by MOEEBIUS project. This paper reflects only the authors’ views and the Commission is not responsible for any
use that may be made of the information contained therein.
Keywords:
- Engineering management
- Multiple-criteria decision analysis
- Christian ministry
- Efficient energy use
- Control engineering
- Reinforcement learning
- Commission
- Sustainability
- Engineering
- European union
- Mathematical model
- Decision analysis
- Dynamical systems theory
- Gaussian process
- Model predictive control
- Supervisory control
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- Cite
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