Terms and definitions on affordable and sustainable housing *

Performance Gap in Retrofit

Area: Design, planning and building

The performance gap in retrofit refers to the disparity between the predicted and actual energy consumption after a retrofit project, measured in kWh/m2/year. This discrepancy can be substantial, occasionally reaching up to five times the projected energy usage (Traynor, 2019). Sunikka-Blank & Galvin (2012) identify four key factors as contributing to the performance gap: (1) the rebound effect, (2) the prebound effect, (3) interactions of occupants with building components, and (4) the uncertainty of building performance simulation outcomes. Gupta & Gregg (2015) additionally identify elevated building air-permeability rates as a factor leading to imbalanced and insufficient extract flowrates, exacerbating the performance gap. While post occupancy evaluation of EnerPhit—the Passivhaus Institut certification for retrofit—has shown far better building performance in line with predictions, the human impact of building users operating the building inefficiently will always lead to some sort of performance gap (Traynor, 2019, p. 34). Deeper understanding of the prebound effect and the rebound effect can improve energy predictions and aid in policy-making (Galvin & Sunikka-Blank, 2016). Therefore, the ‘prebound effect’ and the ‘rebound effect’, outlined below, are the most widely researched contributors to the energy performance gaps in deep energy retrofit.   Prebound Effect The prebound effect manifests when the actual energy consumption of a dwelling falls below the levels predicted from energy rating certifications such as energy performance certificates (EPC) or energy performance ratings (EPR). According to Beagon et al. (2018, p.244), the prebound effect typically stems from “occupant self-rationing of energy and increases in homes of inferior energy ratings—the type of homes more likely to be rented.” Studies show that the prebound effect can result in significantly lower energy savings post-retrofit than predicted and designed to achieve (Beagon et al., 2018; Gupta & Gregg, 2015; Sunikka-Blank & Galvin, 2012). Sunikka-Blank & Galvin’s (2012) study compared the calculated space and water heating energy consumption (EPR) with the actual measured consumption of 3,400 German dwellings and corroborated similar findings of the prebound effect in the Netherlands, Belgium, France, and the UK. Noteworthy observations from this research include: (1) substantial variation in space heating energy consumption among dwellings with identical EPR values; (2) measured consumption averaging around 30% lower than EPR predictions; (3) a growing disparity between actual and predicted performance as EPR values rise, reaching approximately 17% for dwellings with an EPR of 150 kWh/m²a to about 60% for those with an EPR of 500 kWh/m²a (Sunikka-Blank & Galvin, 2012); and (4) a reverse trend occurring for dwellings with an EPR below 100 kWh/m²a, where occupants consume more energy than initially calculated in the EPR, referred to as the rebound effect. Galvin & Sunikka-Blank (2016) identify that a combination of high prebound effect and low income is a clear indicator of fuel poverty, and suggest this metric be utilised to target retrofit policy initiatives.   Rebound Effect The rebound effect materializes when energy-efficient buildings consume more energy than predicted. Occupants perceive less guilt associated with their energy consumption and use electrical equipment and heating systems more liberally post-retrofit, thereby diminishing the anticipated energy savings (Zoonnekindt, 2019). Santangelo & Tondelli (2017) affirm that the rebound effect arises from occupants’ reduced vigilance towards energy-related behaviours, under the presumption that enhanced energy efficiency in buildings automatically decreases consumption, regardless of usage levels and individual behaviours. Galvin (2014) further speculates several factors contributing to the rebound effect, including post-retrofit shifts in user behaviour, difficulties in operating heating controls, inadequacies in retrofit technology, or flawed mathematical models for estimating pre- and post-retrofit theoretical consumption demand. The DREEAM project, funded by the European Union, discovered instances of electrical system misuse in retrofitted homes upon evaluation (Zoonnekindt, 2019). A comprehensive comprehension of the underlying causes of the rebound effect is imperative for effective communication with all retrofit stakeholders and for addressing these issues during the early design stages.   Engaging residents in the retrofit process from the outset can serve as a powerful strategy to mitigate performance gaps. Design-thinking (Boess, 2022), design-driven approaches (Lucchi & Delera, 2020), and user-centred design (Awwal et al., 2022; van Hoof & Boerenfijn, 2018) foster socially inclusive retrofit that considers Equality, Diversity, and Inclusion (EDI). These inclusive approaches can increase usability of technical systems, empower residents to engage with retrofit and interact with energy-saving technology, and enhance residents’ energy use, cultivating sustainable energy practices as habitual behaviours. Consequently, this concerted effort not only narrows the performance gap but simultaneously enhances overall wellbeing and fortifies social sustainability within forging communities.

Created on 08-09-2023

Author: S.Furman (ESR2)


* This vocabulary consists of definitions of key terms related to the combined research conducted by the 15 early-stage researchers. Each term has multiple definitions, each connected to one of the three main research areas: Design, Construction and Planning; Community Involvement; and Policy and Funding.

The joint construction of this vocabulary allows the researchers' projects to be interwoven. As such, the vocabulary is a tool for conducting transdisciplinary research on affordable and sustainable housing.

Entries are reviewed by RE-DWELL researchers and supervisors. The vocabulary is updated regularly.