Space heating control using acceptable set-point temperature estimation by a statistical approach in the lyon smart community project

Abstract

Since the energy consumption of space heating accounts for more than 40% of the non-residential energy consumption and about 70% of the residential energy consumption, respectively, in the EU region, it is important to develop energy-saving technologies for space heating control, which is one of the main functions of building automation, in order to realize zero energy buildings (ZEBs), which are expected to be developed in the EU and worldwide. In a smart community project in Lyon, France, which was a joint project by Japan and France, we evaluated energy-saving technologies for space heating based on the data obtained by a Home Energy Management System (HEMS) introduced to the residential area of a building constructed in Lyon, France. Using this HEMS, we have carried out a field test of a new space heating control method using acceptable set-point temperature estimation by a statistical approach (data-driven method), which learns occupants' thermal feedbacks and makes use of them for control. In the field test, based on the data collected by the HEMS, we have obtained the evaluation result for 21 of the 36 apartments in the residential area. We have confirmed that the proposed method lowered minimum acceptable set-point temperatures in 15 apartments and the average energy-saving rate of the proposed method was estimated as 22.1%. Our result also shows that the proposed method can follow the change of occupants' preferred set-point temperature and update the minimum acceptable set-point temperature by learning their feedbacks.