Energy Efficiency improvement by the way of identification with sensors use

Abstract : To reduce energy consumption in buildings many efforts have been made to find new approaches to manage energy consumption in buildings. In this light, the intelligent management of power consumption in buildings is a major concern for providers and consumers of energy. Model identification to optimize the energy consumption One of the most important problems in many areas of science and engineering is the modeling of input/output properties of a system. Modeling systems based on the connection input/output is often referred to as system identification. These models establish relations between the factors given by a sensors network. Machine learning to optimize the energy consumption. The challenge to reduce energy consumption is not limited only to the structural and physical nature of the building; we must also take into account the users’ behavior. In fact, energy efficiency in buildings can be defined as the ratio between energy consumption and users‘ comfort. But, while it is simple to measure the energy consumed using different sensors, comfort is much harder to assess. In this context, it is necessary to develop new control systems more advanced than traditional control systems. The goal is to use machine learning methods in order to control the services of a building intelligently while taking into account its actual usage and not only its physical properties.
Type de document :
Communication dans un congrès
28th European Conference on Operational Research, Jul 2016, Poznan, Poland
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Contributeur : Magalie Prudon <>
Soumis le : mardi 13 juin 2017 - 14:36:13
Dernière modification le : mardi 27 mars 2018 - 16:06:19

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  • HAL Id : hal-01538376, version 1

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Ghassene Jebali, Therese Peffer. Energy Efficiency improvement by the way of identification with sensors use. 28th European Conference on Operational Research, Jul 2016, Poznan, Poland. 〈hal-01538376〉

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