Abstract/Summary

Peaks in electricity demand bring about significantly negative environmental and economic impacts. This is because if a vast number of users is consuming electricity at the same time, suppliers have to activate power plants with higher greenhouse gas emissions and higher system costs. In Europe, the residential sector is responsible for about one third of overall electricity demand and up to 60% of peak demand. During peak demand, electricity prices in wholesale markets could fluctuate from less than €0.04/kWh to as much as €0.35/kWh (Torriti, 2015). Whilst the volume of electricity demand relates to many factors (e.g. weather, type of appliances, types of building), patterns throughout the day are a direct reflection of people’s activities. A simple example derives from the substantial difference between residential electricity load curves for weekdays and weekends. During the same season the weather can be equal at the weekend compared with the weekday. Everything else remains the same between a day of the week and the weekend: building, appliances, fuel substitution, price of energy and appliance control, and even the moment of the day in which sunlight is present or absent. Changes between weekday and weekend are triggered by people’s activities. In the energy economics literature, traditionally electricity demand has been seen as relatively inelastic to price changes in the short term. Empirical work on dynamic energy tariffs has been increasing in recent years and shows that price is often an insufficient levy to ‘shift’ peaks and, hence, improve the flexibility of energy demand. Information about the timing of people’s activities can reveal something around the flexibility of people’s patterns in peak demand. I will present an analysis of the 2014-2015 Office for National Statistics National Time Use Survey with a view to derive an intrinsic flexibility index based on: how synchronised activities are within the family and with the rest of the country we live in; how many activities requiring electricity we share with others; and how fragmented days are in terms of number and duration of electricity-related activities. Findings will show how greenhouse gases’ intensities and flexibility to shift activities vary throughout the day. Some reflections will also be drawn on the application of this research to work on price elasticity as the analysis will show how introducing a dummy variable based on the intrinsic flexibility index improves the accuracy of price elasticity predictions.