Non-linear Model Predictive Control for Smart Heating of Buildings

Smart and flexible operation of components in district heating systems can play a crucial role integrating larger shares renewable energy sources systems. Buildings are one the that will enable flexibility by using intelligent operation. Recent work suggests such improved at same time increase thermal comfort lower economic costs. We have digitalised system Danish school adding IoT devices, as smart thermostats temperature sensors to demonstrate possibilities making buildings smart. Based on experimental data, this paper introduces non-linear grey-box model dynamics building. A predictive control method is presented for thermostatic set-point building's radiators. building algorithm, simulation studies carried out show potential When used lowering return results suggest operational costs be lowered around 10% control.