Energy Poverty Indicators: Conceptual Issues - Part I: The Ten-Percent-Rule and Double Median/Mean Indicators

Schuessler, Rudolf

doi:10.2139/ssrn.2459404

Cited by 46 publications

(41 citation statements)

References 18 publications

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“…Subsequently, there is a recently growing literature on energy poverty in the UK, such as Boardman (2010), Chawla and Pollitt (2013), Moore (2012), and Waddams Price et al (2012), on other European Union (EU) countries such as Austria (Brunner et al, 2012), Germany (Heindl and Schuessler, 2015;Schuessler, 2014), and Spain (Phimister et al, 2015), and as a comparative study across the EU (Bouzarovski et al, 2012;Thomson and Snell, 2013). …”

Section: Measuring Energy Povertymentioning

confidence: 99%

“…To measure energy poverty, we employ the approach of energy budget shares discussed earlier. Following the conventional definition, a household is in energy poverty if it spends over 10% of its income on energy expenses (costs) (Boardman, 1991(Boardman, , 2010DECC, 2010;Heindl and Schuessler, 2015;Pachauri et al, 2004;Phimister et al, 2015;Schuessler, 2014). More concretely, our definition (hereafter the 10% measure) is a variant of the headcount ratio index P, in which the terms are the energy cost-income ratios of households (E i /Y i ) and the poverty line (z) equals 0.1. households.…”

Section: Energy Poverty In Japanmentioning

confidence: 99%

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Measuring energy poverty in Japan, 2004–2013

Okushima

2016

Energy Policy

128

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Section: Measuring Energy Povertymentioning

confidence: 99%

Section: Energy Poverty In Japanmentioning

confidence: 99%

Measuring energy poverty in Japan, 2004–2013

Okushima

2016

Energy Policy

128

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“…A nation's energy expenditure threshold is chosen as from 10% to 15% of household income globally [8], [9]. Therefore, any household in a nation that spends above the approved nation's energy expenditure threshold is considered to be energy-poor [8], [10].…”

Section: Introductionmentioning

confidence: 99%

Optimization of energy expenditure in smart homes under time-of-use pricing

Longe

Ouahada

Rimer

et al. 2015

2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA)

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Growing peak demand has necessitated the introduction of Time-of-Use (TOU) pricing to Demand Side Management (DSM) in order to cause some peak demand to be shifted from peak to off-peak periods. Therefore, in this work, a Daily Maximum Energy Scheduling (DMES) -DSM technique is proposed. The DMES-DSM device is proposed to be installed into consumers' smart meters and schedule energy consumption for smart appliances. The DMES-DSM technique was verified with real household data and shown to be capable of optimizing households' monthly energy expenditure below approved national energy expenditure threshold and also offer Peak Demand Reduction (PDR). It offered the household considered an average monthly financial savings of 22.44% and 36.73% in summer and winter respectively on electricity bills. Utility can also benefit from the PDR for grid stability and sustainability. Also, the optimized consumption pattern differs only slightly from initial consumption pattern for enhanced consumer satisfaction. Index Terms--DailyMaximum Energy Scheduling (DMES), Demand Side Management (DSM), Household income, Smart appliances, Time-of-Use (TOU).

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“…In recent years, there are further studies, such as Boardman (2010), Chawla and Pollitt (2013), Hills (2011Hills ( , 2012, Moore (2012), and Waddams Price et al (2012). There is also literature on other European Union (EU) countries such as Austria (Brunner et al, 2012), Germany (Schuessler, 2014;Heindl and Schuessler, 2015), Spain (Phimister et al, 2015), and a comparative study across the EU (Thomson and Snell, 2013), whereas there are almost no studies outside the European countries, such as in Japan. 4 increased the energy costs in recent years, which are passed on to the households in the form of higher energy prices, especially for electricity.…”

mentioning

confidence: 99%

How Can We Gauge Energy Poverty? A Multidimensional Approach

Okushima

2016

SSRN Journal

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This paper presents a new approach to measuring energy or fuel poverty for developed countries. As such, it develops a multidimensional energy poverty index (MEPI), which can evaluate energy poverty from a multidimensional angle.The MEPI is composed of three attributes (dimensions) of energy poverty in developed countries: energy costs, income, and energy efficiency of housing. We apply this measure to gauge energy poverty in Japan after the 2000s, focusing on the year of the Great East Japan Earthquake and the Fukushima nuclear accident.Based on unique microdata, the results show that energy poverty has been aggravated in Japan since the 2000s. Analyzing the situation by household type, we can categorize mother-child and single-aged households, in particular, as vulnerable to energy poverty. In addition, the results indicate the severe impact of energy price hikes after the Fukushima accident on energy poverty aggravation, especially for vulnerable households.

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Energy Poverty Indicators: Conceptual Issues - Part I: The Ten-Percent-Rule and Double Median/Mean Indicators

Cited by 46 publications

References 18 publications

Measuring energy poverty in Japan, 2004–2013

Measuring energy poverty in Japan, 2004–2013

Optimization of energy expenditure in smart homes under time-of-use pricing

How Can We Gauge Energy Poverty? A Multidimensional Approach

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