A Heating Controller Designing Based on Living Space Heating Dynamic’s Model Approach in a Smart Building

Abstract

Most already advanced developed heating control systems remain either in a prototype state (because of their relatively complex implementation requirements) or require very specific technologies not implementable in most existing buildings. On the other hand, the above-mentioned analysis has also pointed out that most smart building energy management systems deploy quite very basic heating control strategies limited to quite simplistic predesigned use-case scenarios. In the present paper, we propose a heating control strategy taking advantage of the overall identification of the living space by taking advantage of the consideration of the living space users’ presence as additional thermal sources. To handle this, an adaptive controller for the operation of heating transmitters on the basis of soft computing techniques by taking into account the diverse range of occupants in the heating chain is introduced. The strategy of the controller is constructed on a basis of the modeling heating dynamics of living spaces by considering occupants as an additional heating source. The proposed approach for modeling the heating dynamics of living spaces is on the basis of time series prediction by a multilayer perceptron neural network, and the controlling strategy regarding the heating controller takes advantage of a Fuzzy Inference System with the Takagi-Sugeno model. The proposed approach has been implemented for facing the dynamic heating conduct of a real five-floor building’s living spaces located at Senart Campus of University Paris-Est Créteil, taking into account the occupants of spaces in the control chain. The obtained results assessing the efficiency and adaptive functionality of the investigated fuzzy controller designed model-based approach are reported and discussed.

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“…According to the authors, this solution provides safety, positively influences costs, and increases efficiency, performance, and useability. The authors of the paper [22] propose a different strategy of heating control, emphasizing the integration of user presence as an additional factor in managing heating within the living space. They present a flexible heating control system that adapts to diverse occupants within the heating network.…”

The Impact of Thermo-Modernization and Predictive Regulation on Heat Energy Consumption and Emission of Pollutants into the Atmosphere - The Case of Prefabricated Buildings

“…Another important aspect is the location of the building in relation to world directions and the density of buildings in the surroundings [11][12][13][14]. Scientific studies have shown that the operating habits and routine of residents with respect to their temperature preferences also have a significant impact on the heat demand [15][16][17]. The energy efficiency of a building depends not only on the structure of the building itself, but also on the behavior of its inhabitants.…”