Households’ self-selection of dynamic electricity tariffs

Ericson, Torgeir

doi:10.1016/j.apenergy.2011.01.024

Cited by 61 publications

(23 citation statements)

References 16 publications

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“…The demand side management potential and effectiveness of pricebased Demand Response (DR) techniques have been analysed in some researches [4][5][6]. Moreover, several dynamic tariffs have been introduced and implemented for residential electricity customers in order to enhance the efficiency of DR programs and improve the operational issues at power networks [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Novel model for defining electricity tariffs using residential load profile characterisation

Davarzani

Pisică

Lipan

2018

IJRET

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In recent years, great attention towards enabling future smart grid functionalities in distribution networks creates significant changes in electricity load profiles. These changes require a new advanced paradigm in electricity pricing and tariffs definition aiming to increase the potential of responsiveness demand. This paper aims to propose a new model for designing residential electricity tariffs using their load profile clustering and characterization, taking into account social, technical and educational factors alongside the financial incentives. The methodology is based on estimation of the potential of demand responsiveness to dynamic pricing over time for different cluster of households with similar electricity consumption patterns. In this regard, different time of use pricing bands has been considered and compared with fixed price tariffs. Moreover, a baseline demand for each cluster of households has been determined based on the elasticity of demand to different static tariffs. The results show that the proposed model can provide distribution network operators (DNOs) and suppliers with a basic and general outline of defining more effective dynamic pricing schemes that reflect intermittent nature of residential demand.

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Section: Introductionmentioning

confidence: 99%

Novel model for defining electricity tariffs using residential load profile characterisation

Davarzani

Pisică

Lipan

2018

IJRET

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“…Incentive based DR programs pay participating customers to reduce their loads at times requested by the program sponsor, triggered either by a grid reliability program or high electricity prices [1]. Recently, a massive focus has been made on DR programs which aim to electricity price reduction, transmission line congestion resolving, security enhancement, and market liquidity [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Improving direct load control implementation by an inititative load control method

Rastegar

Fotuhi‐Firuzabad

Moeini‐Aghtaie

2013

18th Electric Power Distribution Conference

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Demand response (DR) as a state-of-the-art program is accommodated in the energy efficiency contexts of the smart grid. Lack of the customer knowledge about how to respond to the time-differentiated tariffs and offered controlling signals is the major obstacle in the way of broad DR implementing. As a solution, an optimization method, namely load control (LC), is proposed to automatically control the onloff status of the responsive appliances in a smart home. This paper focuses on the direct load control (DLC) program in the category of incentive-based DR programs. LC is extended to consider inconvenience cost of the DLC implementation for DLC program participants. Outputs of the extended LC would be an advice for the customer to determine whether it is financially profitable to participate in the offered DLC program or not. Numerical studies are effectuated to investigate different features of the LC and DLC program.

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“…Notwithstanding, this continues to be an issue, as the growing literature would indicate, in view of the constraints in energy supply facing modern society (e.g. Newsham and Bowker, 2010;Ericson, 2011;and Vassileva et al 2012). There is a prevalent view in literature that TOU rates generally reduce peak demand and the need for capacity, even though there is lack of consensus about the magnitude of that effect (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…The overall effect is dependent on the changes in consumption patterns. Higher flexibility in the consumption of electricity encourages the choice of differentiated rates (Ericson, 2011). Switching from peak periods to other periods depends on the consumer profile (behavior, sensitivity and consumer attitudes), such as noted by Bartusch et al (2011), and the available structure of TOU rates (Tanaka, 2006).…”

Section: Introductionmentioning

confidence: 99%

Household Preferences for Time-of-Use Rates in the Portuguese Electricity Market

Marques

Fontes

Fuinhas

2012

Energy Studies Review

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This paper contributes to the debate about peak-load pricing by making an analysis of the residential electricity market in Portugal. The results were built on techniques of logit regression complemented by quantile regression. We estimate the probability of choosing the Time-Of-Use electricity rate and the probability of reducing the Monthly Costs of Electricity by switching the rate for different consumer profiles. Factors such as consumer behaviour and knowledge are determinant when it comes to choosing differentiated rates. Our results suggest guidelines for defining policy measures that will promote an effective change in consumption periods and rate choices.

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Households’ self-selection of dynamic electricity tariffs

Cited by 61 publications

References 16 publications

Novel model for defining electricity tariffs using residential load profile characterisation

Novel model for defining electricity tariffs using residential load profile characterisation

Improving direct load control implementation by an inititative load control method

Household Preferences for Time-of-Use Rates in the Portuguese Electricity Market

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