Parameter Simplification of RC Network Models with Radiant Floor Heating in Residential Buildings

This study presents a parameter simplification method for a grey-box model based on a radiant floor heating system in residential buildings. The grey-box model requires numerous parameters to accurately reflect the physical and thermal characteristics of buildings, resulting in complex modeling and increased computational costs. To address this challenge, the study develops a method to simplify the model structure, thereby improving computational efficiency while maintaining physical interpretation. The existing grey-box model consists of 24 thermal resistances and 17 thermal capacities. In contrast, the proposed simplified models, 24R-8C and 16R-6C, reduce the number of parameters from 24R-17C to 24R-8C and 16R-6C, respectively, enhancing computational efficiency. This simplification minimizes costs while delivering satisfactory prediction performance. The average root mean square error (RMSE) for indoor air temperature and floor surface temperature in the base model (24R-17C) was approximately 0.51℃. The two simplified models, 24R-8C and 16R-6C, demonstrated RMSE values of approximately 0.51℃ and 0.63℃, respectively. The outcomes of this study are expected to contribute to practical energy-saving effects when the proposed models are applied to real-time heating control via model predictive control (MPC).