Dynamic online optimization of a house heating system in a fluctuating energy price scenario

We consider dynamic optimization of the energy consumption in a building with energy storage capabilities. The goal is to find optimal policies which minimize the cost of heating and respect operational constraints. The main complication in this problem is the time-varying nature of the main disturbances, which are the energy price and outdoor temperature. To find the optimal operable policies, we solve a moving horizon optimal control problem assuming known disturbances. Next, we proposed simple implementation based on feedback control, which gives a near-optimal operation for a range of disturbances. The methods were successfully tested in simulations, which show that there is a great economical gain in using dynamic optimization for the case of variable energy price.