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 fuel poverty


How AI technology can alleviate energy poverty

#artificialintelligence

Cold winter days are the hardest to endure for people suffering energy poverty. "I was getting lethargic sitting still to keep warm," says one. I was saving up the money. Mentally, I was losing my health, cutting down on so many things," says another. "I was holding off with the laundry, even holding off going out looking for a job because you need clean clothes." These are cries for help from people who have contacted the Fuel Bank Foundation over the past year. The charity provides emergency credit to those struggling to pay their energy bills. Requests for support have increased by 23 per cent since the start of the coronavirus pandemic. Worse still, the foundation says self-disconnection, where households switch off their power supply completely, is a growing problem. Choosing between heating and eating, or between having power or going into debt, are decisions increasing numbers of people are having to make. It has been a long, tough winter. Unemployment currently stands at 5.1 ...


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

arXiv.org Machine Learning

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.