Hybrid model for building performance diagnosis and optimal control

This paper proposes a new hybrid model for automatic diagnostics and optimal supervisory control. Detailed physical parameters represent half of the model and identified parameters describe another half. That hybrid model can be used to predict accurately the cooling and heating energy consumption of buildings in a wide range of operation conditions.