Does Differential Off-Peak Electricity Pricing Affect Usage? John Williams, Rob Lawson and Paul Thorsnes School of Business

Synopsis of Project Mercury Energy contacted Otago University for help with a pricing experiment Rob and Paul responded and set up study, John joined later Question: Does pricing household electricity differently at peak and off-peak times induce “load shifting”? Peaks strain the physical infrastructure and have negative financial impacts on retailers

Study Design: Experimental Groups Five experimental groups (four treatment groups + one control group) NameInformationPrice DifferenceOn-PeakOff-Peak HighYes20¢ MedYes10¢ LowYes4¢ InfoYesNone ControlNone “Off-peak” is from 7PM to 7AM weekdays; weekends & public holidays

Study Design: Sample Approximately 400 households in Auckland (Pakuranga)Pakuranga Recruited by Mercury Energy Allocated by Mercury to experimental groups All participants got: – A monthly report of usage, including daily and monthly peak and off-peak usage – Access to usage info via the Web – A list of energy-saving tips

Study Design: Data Study ran from 1 August 2008 to 31 July 2009 Mercury supplied us with daily readings for both peak and off-peak periods (i.e. two readings per day for each household) Also supplied data for corresponding period one year before the experiment began Technical problems with data: only December 2007 onwards is usable

Energy Usage: Seasonality

Proportion of Off-Peak Use Christmas ANZAC Waitangi Easter

Group Effect Start of Experiment

Panic! Identified systematic variations across experimental groups which confound results Significant amount of unusable data Solution: compare within households – Examine the differences in energy use in a period (week, month, year) during the experiment and compare with the corresponding period before the experiment – Scale: proportional change from baseline (+ve values indicate increase in study period) (Before – During) / Before

Total Usage Change

Proportional Usage Change

Prop. Off-Peak Usage Change

Differences by Year: Total (%)

Differences by Year: Prop Off-Peak(%)

Summary Systematic differences between experimental groups complicates analysis enormously – Not possible to directly detect influence of pricing Comparison to previous period is suspect – Don’t know if change was part of a pre-existing trend Solution: comparison to baseline, expressed as a proportion, puts all groups on common metric and allows comparison between groups Result: possibly a conservation effect (“significant” but R 2 tiny); no evidence of a switching effect

Where to from here? Caveats: data is difficult to deal with, i.e. Missing values and outliers — have not fully investigated impacts of this yet May need to take other non-random differences into account (characteristics of households) Not 100% (or even 95%) confident of results yet Mercury ran a post-survey, but we haven’t had time to search it for clues yet... Some households did use less energy, and some used more off-peak: what makes them different from those who didn’t?

Tentative Conclusions Absolute magnitude of financial incentives may have been too low — but note the large price difference is outside the margins that a retailer could realistically offer Attitudes and values may have bigger impact than $$$, also could be interactions (further analysis)