Parameter identification and model based predictive control of temperature inside a house

HVAC (Heating, Ventilation and Air Conditioning) systems used for heating or cooling buildings, consume a considerable amount of energy. To optimize the energy consumption, the behavior of occupants must be changed. This can be achieved by providing information and suggestions to occupants. A first step is developing of a less expensive and non-invasive measurement system and metering of the electricity and heat consumed. Based on collected experimental data, it can identify the parameters of a thermal model of the house. The model obtained will be used to simulate different aspects that can help to reduce the energy consumption. This paper presents a simple solution for thermal modeling of a house which includes experimental identification of the model's parameters. Such data are used to simulate the thermal behavior of the house and to obtain solutions to reduce energy consumption. In simulation, the control of the thermal system is performed using a model based predictive control algorithm.