TITLE:
Comparison and Simulation of Building Thermal Models for Effective Energy Management
AUTHORS:
Fatima Amara, Kodjo Agbossou, Alben Cardenas, Yves Dubé, Sousso Kelouwani
KEYWORDS:
Building Control, Inverse Modeling, Building Prediction Model, Simplified Building Models, Parameters Estimation
JOURNAL NAME:
Smart Grid and Renewable Energy,
Vol.6 No.4,
April
30,
2015
ABSTRACT: Energy consumption reduction efforts in the residential buildings sector represent socio-economical, technological and environmental preoccupations which justify advanced scientific research. These lead to use inverse models to describe thermal behavior and to evaluate the energy consumption of buildings. Their principal goal is to provide supporting evidence of enhanced energy performances and predictions. More specifically, research questions are related to building thermal modeling which is the most appropriate in a smart grid context. In this context, the models are reviewed according to three categories. The first category is based on physical and basic principle modeling (white-box). The second offers a much simpler structure which is the statistical models (black-box). The black-box is used for prediction of energy consumption and heating/ cooling demands. Finally, the third category is a hybrid method (grey-box), which uses both physical and statistical modeling techniques. In this paper, we propose a detailed review and simulation of the main thermal building models. Our comparison and simulation results demonstrate that the grey-box is the most effective model for management of buildings energy consumption.