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

Fergus, P and Chalmers, C (2021) Energy Sobriety: A Behavior Measurement Indicator for Fuel Poverty Using Aggregated Load Readings from Smart Meters. In: Towards Energy Smart Homes: Algorithms, Technologies and Applications. Springer, pp. 21-47. ISBN 978-3-030-76476-0

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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.

Item Type: Book Section
Uncontrolled Keywords: cs.LG; cs.LG; cs.CY; eess.SP; stat.ML; I.2; I.5
Subjects: H Social Sciences > HF Commerce > HF5001 Business
H Social Sciences > HD Industries. Land use. Labor
Q Science > QA Mathematics > QA76 Computer software
Divisions: Computer Science & Mathematics
Publisher: Springer
SWORD Depositor: A Symplectic
Date Deposited: 09 May 2023 12:35
Last Modified: 12 Nov 2023 00:50
DOI or ID number: 10.1007/978-3-030-76477-7_2
URI: https://researchonline.ljmu.ac.uk/id/eprint/19475
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