Adaptive HVAC zone modeling for sustainable buildings

Control of energy flows within a building is critical to achieving optimal performance of heating, ventilation and air-conditioning (HVAC) systems. To design optimal HVAC control strategies, a dynamic model of the HVAC system – particularly the building zones that it services – is essential. As analysis of building energy consumption is facilitated by the accurate prediction of indoor environmental conditions, techniques that dynamically model HVAC zones are crucial, and as such, is an active area of research. This paper focuses on real-time HVAC zone model fitting and prediction techniques based on physical principles, as well as the use of genetic algorithms for optimization. The proposed approach is validated by comparing real-time HVAC zone model fitting and prediction against the corresponding experimental measurements. In addition, comparison with prediction results using an algorithm based on feedback-delayed Kalman filters has demonstrated the superiority of the proposed approach in terms of prediction accuracy.