TY - JOUR
T1 - Closing the energy flexibility gap
T2 - Enriching flexibility performance rating of buildings with monitored data
AU - de-Borja-Torrejon, Manuel
AU - Mor, Gerard
AU - Cipriano, Jordi
AU - Leon-Rodriguez, Angel Luis
AU - Auer, Thomas
AU - Crawley, Jenny
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2024/5/15
Y1 - 2024/5/15
N2 - Quantifying and rating energy flexibility in existing buildings will become increasingly important as building energy services become electrified. Flexibility ratings based on building design specifications have shown potential to complement energy performance certificates and enable the comparison between buildings. However, relying on physical models and standard boundary conditions could lead to a ‘flexibility gap’: a difference between predicted and actual flexibility. This article investigates the incorporation of monitored data into design-based flexibility ratings, using an existing rating methodology and two UK case study domestic buildings. We firstly examine whether the current rating methodology can accept monitored data, and find it is able to apart from the final step of rating. We then devise two methods of calculating the metrics required for the flexibility rating, based not on physical models but on data. Using these methods, we examine the impact of the standard operational modelling assumptions on the flexibility metrics compared to using data-informed inputs, which highlights some discrepancies and some concepts in the flexibility rating methodology for which monitored data may be very difficult to obtain (e.g. recovery time). Finally, we suggest how to improve the usefulness of flexibility ratings by incorporating additional information based on monitored data.
AB - Quantifying and rating energy flexibility in existing buildings will become increasingly important as building energy services become electrified. Flexibility ratings based on building design specifications have shown potential to complement energy performance certificates and enable the comparison between buildings. However, relying on physical models and standard boundary conditions could lead to a ‘flexibility gap’: a difference between predicted and actual flexibility. This article investigates the incorporation of monitored data into design-based flexibility ratings, using an existing rating methodology and two UK case study domestic buildings. We firstly examine whether the current rating methodology can accept monitored data, and find it is able to apart from the final step of rating. We then devise two methods of calculating the metrics required for the flexibility rating, based not on physical models but on data. Using these methods, we examine the impact of the standard operational modelling assumptions on the flexibility metrics compared to using data-informed inputs, which highlights some discrepancies and some concepts in the flexibility rating methodology for which monitored data may be very difficult to obtain (e.g. recovery time). Finally, we suggest how to improve the usefulness of flexibility ratings by incorporating additional information based on monitored data.
KW - Building labelling
KW - Demand response
KW - Demand side management
KW - Energy Flexibility
KW - Energy Flexible Buildings
KW - Flexibility Gap
KW - Flexibility indicators
KW - Performance rating
UR - http://www.scopus.com/inward/record.url?scp=85189754908&partnerID=8YFLogxK
U2 - 10.1016/j.enbuild.2024.114141
DO - 10.1016/j.enbuild.2024.114141
M3 - Article
AN - SCOPUS:85189754908
SN - 0378-7788
VL - 311
JO - Energy and Buildings
JF - Energy and Buildings
M1 - 114141
ER -