Rethinking Real Time Electricity Pricing

By Hunt Allcott. 2011

499 citations recorded by the source corpus.

Most US consumers are charged a near-constant retail price for electricity, despite substantial hourly variation in the wholesale market price. This paper evaluates the first program to expose residential consumers to hourly real-time pricing (RTP). I find that enrolled households are statistically significantly price elastic and that consumers responded by conserving energy during peak hours, but remarkably did not increase average consumption during off-peak times. The program increased consumer surplus by $10 per household per year. While this is only one to two percent of electricity costs, it illustrates a potential additional benefit from investment in retail Smart Grid applications, including the advanced electricity meters required to observe a household’s hourly consumption.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/38de0fcb3624a99e6d9a2573d083243cb841c0ec

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In Electrical and Electronic Engineering

In Renewable Energy, Sustainability and the Environment

Citations in the corpus

The Long-Run Dynamics of Electricity Demand: Evidence from Municipal Aggregation (2020, background): “4A growing literature investigates the impact of real-time pricing (e.g., Wolak, 2011; Allcott, 2011; Jessoe and Rapson, 2014).”
On demand: Can demand response live up to expectations in managing electricity systems? (2019, background): “ComEd "Energy smart pricing plan" [26] Illinois trial 2003 2006 693”
Smart homes and their users: a systematic analysis and key challenges (2014, background): “Linked in-home displays communicating usage and cost information to end-users enable utilities to charge for electricity at its marginal cost, providing a price signal to shift or curtail demand when supply is expensive or in short supply [4, 42].”
Knowledge is (Less) Power: Experimental Evidence from Residential Energy Use (2014, unknown): “In Figure (1), for example, a DA pricing event was held between noon and 4pm.”
A systematic review of motivations, enablers and barriers for consumer engagement with residential demand response (2020, background): “For example, perceived risk or complexity can deter some consumers from enrolling in real-time pricing (Allcott, 2011), while participants in one trial of dynamic time-of-use pricing said they would be more likely to sign up again if price changes were more predictable (Carmichael et al., 2014).”
A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms (2015, background): “Similar studies are presented in [99], [105], and [130], where time-based schemes in North America, in California and in the city of Chicago, IL, are respectively presented and analyzed.”
An overview of Demand Response: Key-elements and international experience (2017, background): “Regarding small customers (e.g. residential), Allcott [111] indicates that the increase in consumer welfare is not signi ﬁ cant since the electricity costs represent only a small portion of their overall expenses; however, it results in an increase in the overall social welfare.”
The Role of Aggregators in Smart Grid Demand Response Markets (2013, background): “DR can take place at a very fast timescale, almost real-time, it leads to a more stable power grid system and it significantly reduces electricity generation cost and CO2 emissions [1].”
How to engage consumers in demand response: A contract perspective (2013, background): “…on consumer price elasticity shows that the demand side, especially the residential and small and medium-sized enterprise (SME) consumers, is not very active nowadays, even when retail price variation through time of use tariffs is present (e.g. Allcott, 2011; Lijesen, 2007; Torriti, 2012).”
Dynamic electricity pricing - Which programs do consumers prefer? (2013, unknown): “In Germany these tariffs are not common as the regulatory context for them (“Lastabschaltverordnung”) is still within the policy-making process. iv Allcott (2011) evaluated an RTP-scheme and found that participants reduced the demand in high-price periods, but hardly increased it in lower price…”