Environmental and Energy Law Update
        A blog from the attorneys of Verrill

        Dynamic Pricing Triggers EV Owners’ Load Shift to Early Morning Hours

        by Hans C. Eysenbach on June 3, 2019

        Supplying electricity during peak demand, the period of highest customer demand for electricity (typically around 4 – 7 p.m.), increases the costs of supply – both for transmission and distribution utilities and customers. Dynamic pricing is one potential remedy to this economic challenge of electricity supply. A recent study furthers the case for utilities to couple their dynamic pricing programs’ time-of-use electricity pricing with increased customer access to pricing information and recommended conservation actions.

        The National Bureau of Economic Research published a study in February 2019 that charts a variety of courses that transmission and distribution utilities can use in tandem with time-of-use pricing.[1] Those strategies seek to shave peak demand by shifting some of the load to non-peak periods. The study used data compiled in a field experiment in collaboration with a not-for-profit research entity, Pecan Street, and the University of Texas-Austin to gauge the participants’ electricity consumption in response to time-of-use rates.

        The experiment collected data over 2013 and 2014 during (1) the hottest 27 summer days, which coincide with peak electricity prices; and (2) the November – December winter period, when wholesale electricity prices are lowest due to Texas’ high wind generation. Participating households received a $200 incentive to join the study and the opportunity to realize savings in electricity costs from the simulated dynamic pricing model. The dynamic pricing was set as follows:

        • $0.64 / kWh during the summer peak pricing periods (between 4 – 7 p.m.) and
        • $0.02 / kWh at night during the wind production period.[2]

        The study found that customer’s adjusted their electricity usage in response to the dynamic pricing and targeted information prompts in the following ways:

        • modestly reducing usage in response to receiving information about upcoming peak pricing events (e.g., the start of peak demand when wholesale prices are highest);
        • further reducing usage, targeted at specific end-uses, in response to text messages with concrete conservation recommendations (e.g., “Pre-cool your home” or “Do not use your clothes dryer”);
        • decreasing by 14% use during the hottest summer days, saving $0.38 kWh; and
        • households with electric vehicles had “a very strong pattern of load-shifting, with much of electric vehicle charging occurring just before 5 a.m., rather than in the evening hours,” in response to the reduced nighttime price in the winter periods.

        Pecan Street provided access to data it developed through ongoing relationships with 280 households in Austin that have allowed monitoring of their household energy use through advanced metering at the circuit level, metering major appliances (e.g., air conditioners and heating units) and rooms in a residence. The area of study in Austin has relatively high levels of electric vehicle penetration (36%), which according to the researchers provides “foresight into a likely future in which the transportation sector and electricity grid are more closely interlinked.” That future, if it includes dynamic pricing coupled with access to information and cost saving recommendations, could provide savings to utilities and customers.


        [1] Burkhardt, Gillingham, and Kopalle, Experimental Evidence on the Effect of Information and Pricing on Residential Electricity Consumption, National Bureau of Economic Research (Feb. 2019) (http://environment.yale.edu/gillingham/PricingInformation.pdf).

        [2] The experiment did not actually change participants’ electric rates. Rather it credited funds or debited them from a credit account, based on whether actual monthly charges exceeded or fell below charges using experimental rates. After the two-year experiment, the funds in the accounts were paid out, at an average of $230 to each household.

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