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An Assessment of the Key Performance Indicators (KPIs) of Energy Efficient Retrofits to Existing Residential Buildings

Author

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  • Orlaith McGinley

    (MaREI Centre, Ryan Institute & School of Engineering, College of Science and Engineering, National University of Ireland, H91 TK33 Galway, Ireland
    Energy Resilience and the Built Environment (ERBE) Centre for Doctoral Training, National University of Ireland, H91 TK33 Galway, Ireland)

  • Paul Moran

    (MaREI Centre, Ryan Institute & School of Engineering, College of Science and Engineering, National University of Ireland, H91 TK33 Galway, Ireland)

  • Jamie Goggins

    (MaREI Centre, Ryan Institute & School of Engineering, College of Science and Engineering, National University of Ireland, H91 TK33 Galway, Ireland
    Energy Resilience and the Built Environment (ERBE) Centre for Doctoral Training, National University of Ireland, H91 TK33 Galway, Ireland)

Abstract

Quantifying the wider benefits of energy efficient building retrofits is crucial to incentivise householder retrofit investments. This research recognises the value of key performance indicators (KPIs) for assessing and demonstrating retrofitting benefits and provides an assessment of KPIs for evaluating retrofits. An integrated framework for evaluating retrofits using a set of economic, social, and environmental KPIs is proposed. This KPI framework is then applied in a pre- and post-retrofit assessment of five case study dwellings located in Ireland, revealing its usefulness in demonstrating the wider benefits of retrofitting to householders, with a view to driving retrofit investment. Three of these case study dwellings had state-of-the-art retrofit technologies installed as part of the works, including heat pumps and solar PV systems. In addition to demonstrating the wider benefits of retrofitting, the framework allowed for the identification of potential causes for differences in performance of these technologies across households, as well as patterns of underperformance. Such insights are useful for the future design of these technologies and retrofit packages, as well as policy measures, which support householders in the adoption and use of these measures. The results demonstrate that householders experience various benefits from retrofitting. Showcasing the different benefits that householders receive from retrofitting, and their satisfaction with the retrofit works, can serve to de-risk retrofit investments, and inspire others to seek similar benefits through retrofitting. Applying the developed framework to a larger, comparable sample size, can distinguish the retrofit packages, which perform best across the KPIs and various household profiles. Furthermore, the application of the developed framework can serve as an evidence base for retrofit designers, contractors, and policy makers in the design of retrofit packages and policy measures that will maximise the benefit for householders.

Suggested Citation

  • Orlaith McGinley & Paul Moran & Jamie Goggins, 2022. "An Assessment of the Key Performance Indicators (KPIs) of Energy Efficient Retrofits to Existing Residential Buildings," Energies, MDPI, vol. 15(1), pages 1-26, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:1:p:334-:d:717292
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    Citations

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    Cited by:

    1. Iivo Metsä-Eerola & Jukka Pulkkinen & Olli Niemitalo & Olli Koskela, 2022. "On Hourly Forecasting Heating Energy Consumption of HVAC with Recurrent Neural Networks," Energies, MDPI, vol. 15(14), pages 1-20, July.
    2. Piotr Bórawski & Rafał Wyszomierski & Aneta Bełdycka-Bórawska & Bartosz Mickiewicz & Beata Kalinowska & James W. Dunn & Tomasz Rokicki, 2022. "Development of Renewable Energy Sources in the European Union in the Context of Sustainable Development Policy," Energies, MDPI, vol. 15(4), pages 1-20, February.
    3. Goggins, Gary & Rau, Henrike & Moran, Paul & Fahy, Frances & Goggins, Jamie, 2022. "The role of culture in advancing sustainable energy policy and practice," Energy Policy, Elsevier, vol. 167(C).
    4. Srivastava, Praveen Ranjan & Mangla, Sachin Kumar & Eachempati, Prajwal & Tiwari, Aviral Kumar, 2023. "An explainable artificial intelligence approach to understanding drivers of economic energy consumption and sustainability," Energy Economics, Elsevier, vol. 125(C).
    5. Piotr Bórawski & Aneta Bełdycka-Bórawska & Lisa Holden, 2023. "Changes in the Polish Coal Sector Economic Situation with the Background of the European Union Energy Security and Eco-Efficiency Policy," Energies, MDPI, vol. 16(2), pages 1-17, January.

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