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Selection of Key Parameters for Energy Management of Building Heating Systems

Paper describes 6R2C mathematical modelling approach using dynamic input data from IoT based sensors in order to calculate and predict energy consumption in building and zone level. The developed model is based on five resistances, one capacitance (5R1C) energy consumption calculation model described in ISO 13790:2008 standard and used for calculation of the energy use for the space heating for residential and non - residential buildings. The 5R1C model is improved by separating the infiltration and ventilation resistances, and separating thermal mass into two parts: thermal mass of building walls and internal thermal mass, which leads to a new 6R2C model in order to gain more accurate simulation of the building energy performance. One of the goals was to obtain real experimental measurement data of both heating (winter) and cooling (summer) periods of the building and compare to simulation results. The obtained results validate, that model can be applied in both cases with relatively good precision, and taking into account that models is simplified and for some energy gain calculations doesn't use precise input data.