Data-driven Optimization of Energy Efficiency and Comfort in an Apartment
An important challenge in home automation is the energy efficient optimization of the indoor environment. This relies on the solution of a multi-objective optimization problem where energy efficiency and comfort parameters are maximized simultaneously. This paper presents three data-driven control a...
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| Published in: | 2018 International Conference on Intelligent Systems (IS) pp. 174 - 182 |
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| Main Authors: | , , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01-09-2018
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| Abstract | An important challenge in home automation is the energy efficient optimization of the indoor environment. This relies on the solution of a multi-objective optimization problem where energy efficiency and comfort parameters are maximized simultaneously. This paper presents three data-driven control algorithms based on machine learning techniques, which offer an alternative to traditional control methods. The results demonstrate that some data-driven methods can achieve similar results than rule-based systems. Moreover, they require no prior expert knowledge and have better scalability than standard approaches. |
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| AbstractList | An important challenge in home automation is the energy efficient optimization of the indoor environment. This relies on the solution of a multi-objective optimization problem where energy efficiency and comfort parameters are maximized simultaneously. This paper presents three data-driven control algorithms based on machine learning techniques, which offer an alternative to traditional control methods. The results demonstrate that some data-driven methods can achieve similar results than rule-based systems. Moreover, they require no prior expert knowledge and have better scalability than standard approaches. |
| Author | Vandekerckhove, Steven Ruyssinck, Joeri Van Hoecke, Sofie Avendano, Diego Nieves Deschrijver, Dirk |
| Author_xml | – sequence: 1 givenname: Diego Nieves surname: Avendano fullname: Avendano, Diego Nieves organization: IDLab, Ghent University - imec, Ghent, Belgium – sequence: 2 givenname: Joeri surname: Ruyssinck fullname: Ruyssinck, Joeri organization: IDLab, imec - Ghent University, Ghent, Belgium – sequence: 3 givenname: Steven surname: Vandekerckhove fullname: Vandekerckhove, Steven organization: Renson Ventilation, Waregem, Belgium – sequence: 4 givenname: Sofie surname: Van Hoecke fullname: Van Hoecke, Sofie organization: IDLab, Ghent University - imec, Ghent, Belgium – sequence: 5 givenname: Dirk surname: Deschrijver fullname: Deschrijver, Dirk organization: IDLab, imec - Ghent University, Ghent, Belgium |
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| Snippet | An important challenge in home automation is the energy efficient optimization of the indoor environment. This relies on the solution of a multi-objective... |
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| SubjectTerms | Actuators Atmospheric modeling Deep reinforcement learning Energy efficiency Heating systems Home automation Model predictive control Multi-objective optimization Optimization Ventilation Windows |
| Title | Data-driven Optimization of Energy Efficiency and Comfort in an Apartment |
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