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Advanced Energy Performance Assessment towards Smart Living in Building and District Level

Project Summary

The next generation of Energy Performance Certificates (EPCs) are a promising source of information to achieve a more climate neutral building stock. Improved schemes are required not to show only  data on the building’s energy consumption, but also on their operational performance over the full life cycle.  However, there is still a need of developing more reliable and cost-effective methodologies that address digital tools and smart control systems.

SmartLivingEPC aims to deliver a building certificate through digitalised tools including not only energy, but also sustainability, water consumption, acoustics and human-centric variables. The new procedure will use real data from the overall building’s life cycle for both the “as designed” and “in-use” performance of the building. Additionally, SmartLivingEPC will develop two novel different schemes; one at the building level, and another one at district level where smart grids and the interaction among buildings are considered in the final rating (i.e. street lighting, network services, energy communities, electric vehicles, etc.). The later looks at the single building assessment from broader perspective by including citizen participation and building’s relationship within a neighbourhood/district. Finally, the project will deliver a methodology to certify energy-efficient neighbourhoods preparing for the future decarbonisation of cities. 

IES' Role

IES’ main role is to integrate a Digital Twin framework as well as AI services as part of the energy assessment procedure. Those tools provide accurate and calibrated 3D virtual building models that reduce the gap between the energy use of a building at the design stage and the actual operation.  

The virtual models will be BIM-based and provide both static and dynamic elements of the buildings. They will be connected to an IoT platform gathering data coming from sensors, building systems and smart devices. Thus, the Digital Twins will be automatically updated with real-time profiles and will be also able to predict future operational scenarios and retrofits through AI tools. AI and ML algorithms will be key for the actual end user and enhance buildings energy use. Those techniques will not only lead to behaviour changes, but also to detect anomalies on assets management.

Test Sites

  • NZEB Smart House (Greece)
  • Frederick University Campus (Cyprus)
  • Office NZEB (Lithuania)
  • Energy Community (Spain)

Project Status