Advanced approach assesses a building’s dynamic energy performance in near real time
The EU building sector accounts for 40 % of total energy usage and requires significant renovation to meet the environmental goals set for 2050. Energy performance certificates (EPCs) are used to estimate a building’s energy efficiency, but they often show disparities between estimated and actual energy use. Static calculations fail to accurately depict the dynamic nature of a building’s actual energy use, the impact of occupants and varying boundary conditions. This discrepancy, or performance gap, has led to many proposals. These mostly relate to the use of more dynamic modelling techniques and the assessment of the indoor environment in buildings. This additional data can be used to develop a more reliable certification/assessment scheme. The EU-funded E-DYCE project developed methods and tools to transition from static EPCs to dynamic EPCs (DEPCs), thereby enabling dynamic assessment of the energy efficiency of the European building stock. This involved identifying input data for dynamic assessment, developing dynamic models, measuring actual energy use and creating key performance indicators for assessing building performance.
Closing the gap between simulated and monitored data
The E-DYCE approach promotes low-technology, passive solutions, taking advantage of cloud databases, connected devices and dynamic climatic data. Systems performance and user behaviour – often a major factors in performance gaps – can be corrected and updated through feedback with the E-DYCE approach. “Unlike existing EPCs, E-DYCE allows for near real-time optimisation, ongoing demand management and short-term forecasts,” notes project coordinator Michal Zbigniew Pomianowski. “It also allows modifying a building’s operation based on predicted performance, and therefore avoiding drifting away during operation periods.” The E-DYCE methodology involved four key levels: adjusting the calculation approach to be more dynamic and fed with actual operation conditions, detection of periods with optimised operation potentials based on its real operation under the current conditions, predicting its performance by using the historical data. “We developed a platform, called PREDYCE, that uses EnergyPlus models with real-time weather data and both standard and adapted conditions of use as inputs,” highlights Pomianowski. PREDYCE allows users to confront simulation results with actual measurements, providing a clearer understanding of the existing performance gap in building operation. Algorithms have also been developed for predicting weather and heat energy use over short, medium and long-term periods.
Correlating energy bills with user actions
Energy bills, which arrive infrequently, often do not provide weather-corrected historical performance data. To this end, E-DYCE engages users in building operations through active feedback from sensing and metering technologies. E-DYCE methodology supports more frequent assessments to evaluate a building’s potential for energy flexibility and prosumer nature. This includes assisting in the ability to shift peak hours for heating, cooling and electricity demand, operating buildings without mechanical resources for thermal and atmospheric comfort (free running), and leveraging smart passive technologies to address heating and cooling demands.
Streamlining the transition from static to dynamic models
Transitioning from static to dynamic modelling is not an easy feat. “We provided suggestions to reduce model complexity, considering different facility types and geometries,” explains Pomianowski. “We also introduced a DEPC protocol with separate key performance indicators for tenants and professionals grouped into distributed energy, energy performance signature, thermal and atmospheric comfort and free-running operation.” “Our ultimate goal has been to provide feasible solutions towards closing the performance gap, detect operation improvement potentials and recommend energy renovations,” concludes Pomianowski.
Keywords
E-DYCE, building, energy performance gap, energy use, dynamic models, free running, operational assessment, EPC
