Smart meter, customer choice and profitable time-of-use rate option

Hartway, Rob; Price, S.; Woo, Chi-Keung

doi:10.1016/s0360-5442(99)00040-7

Cited by 68 publications

(31 citation statements)

References 9 publications

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“…First, peak-demand reductions are almost certainly lower than what could be achieved with 100% participation. Second, voluntary CPP tariffs could encourage adverse self-selection such that households with low peak to off-peak ratios benefit from time-varying rates, while those with high peak to off-peak ratios benefit from time-invariant rates (Hartway et al, 1999;Horowitz and Woo, 2006). This situation might cause shortfalls in a utility's cost recovery or violate the primary objective of fairness to ratepayers unless the tariff alternatives properly reflect risk premiums.…”

Section: Mandatory Vs Default or Voluntary Tariffsmentioning

confidence: 99%

Residential implementation of critical-peak pricing of electricity

2007

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This paper investigates how critical-peak pricing (CPP) affects households with different usage and income levels, with the goal of informing policy makers who are -916-654-4328; fax: +1-916-653-3478 Email address: KBHerter@lbl.gov. 1 $50,000 annually were the most likely of the groups to see bill increases -about 5% saw bill increases of 10% or more -suggesting that any residential CPP implementation might consider targeting this customer group for increased energy efficiency efforts.

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Section: Mandatory Vs Default or Voluntary Tariffsmentioning

confidence: 99%

Residential implementation of critical-peak pricing of electricity

2007

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“…Most previous studies of the economic consequences of tariff switching using real power demand data have been made for residential consumers (for example Hartway et al 1999;Commission for Energy Regulation 2011;Rowlands and Furst 2011;Thorsnes et al 2012;Faruqui et al 2013). Hartway et al (1999), using 15 different datasets, and (Borenstein 2007) are two of the few that perform experiments over real demand data from commercial premises.…”

Section: Introductionmentioning

confidence: 99%

“…Hartway et al (1999), using 15 different datasets, and (Borenstein 2007) are two of the few that perform experiments over real demand data from commercial premises. The most frequently examined tariff change is from a FPT to TOUT (Borenstein 2007;Hartway et al 1999; Commission for Energy Regulation 2011; Rowlands and Furst 2011;Faruqui and Sergici 2010;Thorsnes et al 2012;Faruqui et al 2013), but the static to dynamic tariff switch was also studied (Borenstein 2007;Faruqui and Sergici 2010). Borenstein (2007) considered the wealth transfer due to the tariff change in more than 1100 large businesses in the USA.…”

Section: Introductionmentioning

confidence: 99%

Power-use profile analysis of non-domestic consumers for electricity tariff switching

et al. 2015

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For both domestic and non-domestic consumers, dynamic electricity tariffs have been proposed as a way to reduce their energy costs and to facilitate demand-side response. It is difficult for businesses which are tenants to adopt energy efficiency measures; thus, tariff switching is the easier option. Therefore, understanding the limits of the cost saving offered by tariff switching is an important step. This raises two questions: by how much could bills be reduced, and would all consumers benefit equally? Using a dataset of half-hourly electricity readings from more than 7500 British businesses, we performed an empirical analysis to discover which types of businesses might have lower or higher costs when changing between static and real-time tariffs. We identified differences in demand profiles that demonstrate that the decision whether to switch tariff types is a subtle one which may have a significant cost impact. The dataset was aggregated into five categories: Entertainment, Industry, Retail, Social, and Other. Our analytical methods can be used to distinguish the differences between typical electricity demand profiles for small-to medium-sized businesses and sectors in different market options. Our analyses of switching to a real-time tariff suggest that most of those small-to medium-sized businesses that would reduce their annual electricity bill would gain by no more than 10 %. Most of these businesses would gain by less than 5 %. This, we suggest, sets a realistic upper limit of the likely cash savings before energy efficiency, or other measures must be taken to further reduce bills.

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“…Aigner [33] concludes that effective pricing mechanism to change consumers' behavior is among the most important issues to the success of TOU rates. Other studies focusing on the impacts of TOU rates include [7], [34] [35], and [36].…”

Section: The Choice Of Electricity Cost Functionmentioning

confidence: 99%

Optimal scheduling for charging electric vehicles with fixed setup costs.

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Smart meter, customer choice and profitable time-of-use rate option

Cited by 68 publications

References 9 publications

Residential implementation of critical-peak pricing of electricity

Residential implementation of critical-peak pricing of electricity

Power-use profile analysis of non-domestic consumers for electricity tariff switching

Optimal scheduling for charging electric vehicles with fixed setup costs.

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