LGCYSPMLFeb 16, 2020

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

arXiv:2002.12899v11 citations
AI Analysis

This addresses fuel poverty, affecting millions of households globally, by providing a tool for monitoring and intervention, though it appears incremental as it builds on existing smart meter and machine learning approaches.

The paper tackles the problem of fuel poverty by proposing a new behavior measurement indicator that uses smart meter data and machine learning to detect Activities of Daily Living, aiming to identify early signs of financial difficulty and need for support.

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), 4 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 behavior 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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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