Big Data Supported Analytics for Next Generation Energy Performance Certificates

Energy Performance Certificates (EPCs) have been in place since the implementation of the Energy Performance Directive (2010/21/EU) and were envisaged as a tool to raise awareness on energy efficiency in buildings as well as boost energy refurbishments in the building sector. However, they are slowly becoming a bureaucratic checkpoint that has not fully reached its intended objective. Moreover, due to the lack of interoperability in between data sources and the complex management of the EPCs it has been unfeasible up to now to fully exploit the potential of these official documents. In this chapter, the focus will be placed on several challenges surrounding Energy Performance Certificates, and how big data and machine learning applications can support them. By exploiting publicly available data (cadastre, building construction catalogues, climate data) and monitoring data (real time data), five main functionalities will be provided: (1) EPCs checker, (2) EPCs data exploitation and reports generator, (3) energy conservation measures explorer, (4) visualisation of EPCs and estimated energy parameters, and (5) climate change impact on energy use analysis. These functionalities will support regional authorities in charge of EPC management, building managers as well as citizens, tenants and owners to acquire a deeper understanding on the energy use of their and the neighbouring buildings, as well as assure quality in the information provided or gather insights towards future energy refurbishments. This chapter provides a summary of the application of these services in the Castilla y León and Asturias regions in Spain, as deployed within the H2020 projects: MATRYCS “Modular big data applications for holistic energy services in buildings”, BD4NRG “Big data for next generation energy” and I-NERGY “Artificial intelligence for next generation energy”.