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Energy Sobriety: A Behaviour Measurement Indicator for Fuel Poverty Using Aggregated Load Readings from Smart Meters

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Abstract

Fuel poverty affects between 50 and 125 million households in Europe and is a significant issue for both developed and developing countries globally. This means that fuel-poor residents are unable to adequately warm their home and run the necessary energy services needed for lighting, cooking, hot water, and electrical appliances. The problem is complex but is typically caused by three factors: low income, high energy costs, and energy-inefficient homes. In the United Kingdom (UK), four million families are currently living in fuel poverty. Those in series financial difficulty are either forced to self-disconnect or have their services terminated by energy providers. Fuel poverty contributed to 10,000 reported deaths in England in the winter of 2016–2107 due to homes being cold. While it is recognized by governments as a social, public health, and environmental policy issue, the European Union (EU) has failed to provide a common definition of fuel poverty or a conventional set of indicators to measure it. This chapter discusses current fuel poverty strategies across the EU and proposes a new and foundational behaviour measurement indicator designed to directly assess and monitor fuel poverty risks in households using smart meters, Consumer Access Device (CAD) data, and machine learning. By detecting Activities of Daily Living (ADLS) through household appliance usage, it is possible to spot the early signs of financial difficulty and identify when support packages are required.

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Acknowledgements

This work was inspired by an event run in Liverpool where the authors were invited to present at the ‘Better at Home’ workshop run by the National Energy Action (NEA) organization. We would like to particularly thank Matt Copeland and Dr. Jamie-Leigh Rosenburgh at NEA who asked whether we could extend our dementia smart meter framework to include a behaviour measurement indicator for fuel poverty.

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  1. Department of Computer Science, Liverpool John Moores University, Liverpool, UK

    Paul Fergus & Carl Chalmers

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  1. Paul Fergus
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Correspondence to Paul Fergus .

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  1. G-SCOP lab, Grenoble Institute of Technology University of Grenoble Alps, Grenoble, France

    Stephane Ploix

  2. CNRS, Grenoble, France

    Manar Amayri

  3. CIISE, Concordia University, Montreal, QC, Canada

    Nizar Bouguila

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Fergus, P., Chalmers, C. (2021). Energy Sobriety: A Behaviour Measurement Indicator for Fuel Poverty Using Aggregated Load Readings from Smart Meters. In: Ploix, S., Amayri, M., Bouguila, N. (eds) Towards Energy Smart Homes. Springer, Cham. https://doi.org/10.1007/978-3-030-76477-7_2

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