In the UK, the electricity distribution networks and the electricity generation plants are traditionally designed to cater for peak demand. In addition to increasing the need for network reinforcement, growing peak demand also contributes to rising prices and CO2 emissions associated with the operation of peaking generation plants (Hledik et al. 2017; Frontier Economics, 2012). Time-based components of the electricity bill have been applied for several years to commercial customers to reduce their contribution to peak demand. It is anticipated that the Time-of-Use tariffs will be also widely applied to domestic consumers, potentially increasing the bills for some groups of consumers (Cambridge Economic Policy Associates, 2017; Torriti, 2012).
The proposed research work focuses on the analysis of activities from the UK Time Use Survey 2014-2015 to identify the distribution of activities during the evening peak demand periods. Activities are clustered on the basis of household and individual information to identify groups of high and low frequency of energy-related activities occurring during the peak demand period. Clusters of peak time activities are mined using parameters describing the social-demographics, i.e. employment status, level of education, family size, income and age.
The results will demonstrate the relationship between socio-demographic groups. They will draw conclusions on the likelihood of social-demographic groups being worse or better off from the introduction of Time-of-Use tariffs.
Hledik, Ryan, Will Gorman, Nicole Irwin, Michael Fell, Moira Nicolson, and Gesche Huebner. (2017) “The Value of TOU Tariffs in Great Britain : Insights for Decision-Makers.” Vol. I.
Cambridge Economic Policy Associates. (2017) “Distributional Impact of Time of Use Tariffs – Final Report.”
Frontier Economics. (2012) “Domestic and SME Tariff Development for the Customer – Led Network Revolution.
Torriti, Jacopo. (2012) “Price-Based Demand Side Management: Assessing the Impacts of Time-of-Use Tariffs on Residential Electricity Demand and Peak Shifting in Northern Italy.” Energy 44 (1). Elsevier: 576–83. doi:10.1016/j.energy.2012.05.043
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