Monitoring Approaches for New-Generation Energy Performance Certificates in Residential Buildings

Abstract

In 2002, the Energy Performance of Building Directive (EPBD) introduced energy certification schemes to classify and compare building performances to support reaching energy efficiency targets by informing the different actors of the building sectors. However, since its implementation, the Energy Performance Certifications (EPCs) remained unexploited with limited impact on the energy savings targets. In this context, the EPC RECAST project aims at studying a new generation of EPCs with a focus on the residential sector. More in detail, the paper presents and frames a monitoring approach based on low-cost and non-invasive technology for real data collection in existing residential apartments/houses. The method is based on different levels of monitoring selected according to the typology of the building (e.g., detached house, apartment), services (e.g., centralized or local energy generation), and energy vectors (e.g., natural gas or electricity). Three different levels have been identified (named as: basic, medium, and advanced) and for each one, different plug and play monitoring sensor kits have been selected. Six representative pilot buildings have been identified and selected to verify the approach in general and, in particular, the sensors’ applicability and communication, the data reliability, and the monitoring platform. The presented work highlights, on the one hand, the general feasibility of the proposed monitoring approach; on the other, it highlights the difficulty of fully standardizing the sensors kits considering that each building/apartment has specific characteristics and constraints that have to be carefully analyzed. The use of the ultrasonic flow meters represents a good technical option for reducing the cost and the impact on the existing plant system; however, their installation must be verified considering that the logger needs to be powered and the sensors calibrated for collecting reliable data.