Weather Forecast Control for Heating of Multi-Family Buildings in Comparison with Feedback and Feedforward Control

Abstract

Our joint environmental and energy commitments mean we must reduce the building’s energy use. Improved central heating control can play a role in how this is accomplished. There are three common control strategies: feedforward (traditional), feedback, and model predictive control (MPC). The latter two often work in parallel, where feedback uses indoor temperature sensors to adjust the supply water temperature. In contrast, the supply temperature setpoint is continuously calculated in MPC, fed with weather forecasts. The weather forecasts are often highlighted as essential ingredients in MPC, but at the same time, it is emphasized that temperature sensors are used to ensure a pleasant indoor temperature. To an outside observer, it is difficult to determine what is what in such combined control arrangements. Is energy saved because of the room sensors or because of the model? And what role do the weather forecasts play? This study quantifies the impact of the control strategy on energy use and indoor temperature. It concludes that PI-based feedback heating control saves approximately as much energy as MPC, and weather forecasts do not save significantly more energy than real-time weather data but are easier to obtain. The overall results for both control strategies align with the lower end of the result ranges of previous studies. The novelty is that the impact of weather forecasts has been studied separately and that different control strategies are compared against each other based on a model of a typical Swedish multi-family building.