Abstract
This chapter introduces Arcturus, an international database of dynamic pricing and time-of-use pricing studies. It contains the demand response impacts of 163 pricing treatments that were offered on an experimental or full-scale basis in 34 projects in seven countries located in four continents. The treatments included various types of dynamic pricing rates and simple time-of-use rates, some of which were offered with enabling technologies such as smart thermostats. The demand response impacts of these treatments vary widely, from 0 % to more than 50 %, and this discrepancy has led some observers to conclude that we still do not know whether customers respond to dynamic pricing. We find that much of the discrepancy in the results goes away when demand response is expressed as a function of the peak-to-off-peak price ratio. We then observe that customers respond to rising prices by lowering their peak demand in a fairly consistent fashion across the studies. The response curve is nonlinear and is shaped in the form of an arc: as the price incentive to reduce peak use is raised, customers respond by lowering peak use, but at a decreasing rate. We also find that the use of enabling technologies boosts the amount of demand response. Overall, we find a significant amount of consistency in the experimental results, especially when the results are disaggregated into two categories of rates: time-of-use rates and dynamic pricing rates. This consistency evokes the consistency that was found in earlier analysis of time-of-use pricing studies that was carried out by EPRI in the early 1980s. Our analysis supports the case for the rollout of dynamic pricing wherever advanced metering infrastructure is in place.
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Notes
- 1.
Time-varying pricing refers to time-of-use (TOU) rates as well as dispatchable rate structures such as critical peak prices (CPP) and real-time prices (RTP). AMI is only a prerequisite for dynamic pricing programs, whereas TOU rates can be implemented with legacy meters.
- 2.
Federal Energy Regulatory Commission.
- 3.
Faruqui and Sergici [5] and Flaim et al. [9] summarize the results from some recent studies but do not attempt a meta-analysis of the type reported here. A previous meta-analysis, more limited in scope that this one, is contained in Faruqui and Palmer [4]. A comprehensive bibliography on dynamic pricing can be found in Enright and Faruqui [2].
- 4.
Some studies characterize only smart thermostats as enabling technologies as these devices automatically adjust temperature settings without requiring an action from the customers. For the purposes of this chapter, we characterize smart thermostats, energy orbs, and in-home displays as enabling technologies since these devices either automate actions for customers or equip them with information to act on.
- 5.
For a detailed discussion of time-varying rates, see Faruqui et al. [7].
- 6.
For the PTR rate, the effective critical peak price is calculated by adding the peak-time rebate to the rate the customer normally pays during that time period (in the absence of the rebate). This is essentially the opportunity cost of consuming every kWh of electricity.
- 7.
By using MM-estimation, our re-estimated arcs predict impacts that are lower than before.
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Acknowledgment
This chapter is an updated republication of the paper “Arcturus: International Evidence on Dynamic Pricing” by Ahmad Faruqui and Sanem Sergici, The Electricity Journal 26 (7), 55–65. The copyright permission for reusing the paper has been granted by Elsevier. The authors would like to thank Eric Shultz and Isaac Toussie of Brattle for their excellent research assistance in developing Arcturus and to Toni Enright for assistance in editing and formatting the chapter. We have also benefited from numerous discussions on dynamic pricing with Ryan Hledik and Neil Lessem of Brattle. Finally, Faruqui would like to acknowledge his debt to J. Robert Malko (now a professor at Utah state) for instilling in him a love for time-varying rates when both worked in the Electric Utility Rate Design Study at EPRI.
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Faruqui, A., Sergici, S. (2014). Arcturus: An International Repository of Evidence on Dynamic Pricing. In: Mah, D., Hills, P., Li, V., Balme, R. (eds) Smart Grid Applications and Developments. Green Energy and Technology. Springer, London. https://doi.org/10.1007/978-1-4471-6281-0_4
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