Texas in the summer is normally hot. But there are about 14 days per year when it’s really hot—above, say, 95 degrees Fahrenheit.
On those days, people tend to put their air conditioners on full blast just to keep their homes and businesses at a comfortable temperature. When this happens, local electricity providers worry they won’t be able to keep up with demand, since air conditioning units can represent more than half of a household’s electricity usage. So electric utilities call these hot days “critical peak power” periods and try to encourage their customers to go easy on the AC. If people don’t comply, the utility has to buy more power on the open market, which is expensive. Or it has to invest in more generation facilities, just to be prepared for those peak power episodes, which is also expensive (and bad for the environment). A better solution is to convince customers to set their thermostat at 70 instead of 65, but it’s far from clear how to actually get them to do it.
A field experiment from a neighborhood in Austin, Texas may bring us closer to the answer. Designed in part by Praveen Kopalle, the Signal Companies’ Professor of Management at Tuck, the experiment studied 280 households with appliance-level electric meters to understand what types of information could influence them to conserve electricity during critical peak power periods, as well as take advantage of periods when there was an excess of power in the grid. Kopalle, along with Jesse Burkhardt of Colorado State University and Kenneth Gillingham of Yale University, compiled their findings in a new working paper, “Experimental Evidence on the Effect of Information and Pricing on Residential Electricity Consumption.”
Working with the nonprofit organization Pecan Street, Kopalle and his colleagues recruited households from the Mueller neighborhood by providing them with an opportunity to save on their electric bills and receive a $200 sign-up incentive. They randomly divided the households into one control group and four treatment groups. Each treatment group was provided with a different level of information and communication about their electricity usage. Forty-four homes received passive information, in the form of access to an online portal that tracks appliance-level electricity usage. Forty-six homes received a text-message appeal 24 hours prior to every critical peak pricing event (when the price of electricity would be higher). Forty-seven homes received the same text message as the previous group, but with a recommendation added, such as “pre-cool your home,” or “do not use your clothes dryer.” The final group of 62 homes received pricing information via a text message stating: “Tomorrow is a Critical Peak Pricing event. Your experimental electric rate will be $0.64 per kilowatt hour from 4 p.m—7 p.m.” During the months of March, April, May, November, and December, when wholesale electric prices are low at night (because of better conditions for wind power generation), they received a similar text message, but it reminded them of a lower experimental price of two cents per kilowatt hour.
The households in the pricing group reduced their electricity usage by 14 percent, and about three-quarters of that reduction can be attributed to them turning down, or turning off, their air conditioning.
The two-year study, which took place in 2013 and 2014, generated a surfeit of data—more than 300 million observations of electricity usage, representing every appliance in every household, every minute. “To crank through all of that, we needed to use Dartmouth’s new research computer, which has one terabyte of random-access memory,” Kopalle said.
What they discovered was quite surprising. The only form of communication that had any impact on reducing electricity consumption during peak periods was the one that conveyed pricing information; the households pretty much ignored everything else. But the pricing appeal did make a significant impact: the households in the pricing group reduced their electricity usage by 14 percent, and about three-quarters of that reduction can be attributed to them turning down, or turning off, their air conditioning. A third significant finding is related to the pricing appeals about the lower nighttime prices. The appeal merely notified customers of the reduced price, and people began re-arranging their daily schedules to take advantage of it. “We could see that people began washing their clothes more between 10 p.m. and 6 a.m., and using the furnace more during that time,” Kopalle explained. “They were able to shift their loads to the off-peak periods.”
Inside this finding was another important discovery: households in the pricing group who had electric vehicles seemed to have programmed their cars to charge after 10 p.m., with most of the charging occurring just before 5 a.m. “This pattern of price-induced electric vehicle load shifting towards the early morning hours when wholesale electricity prices are low and away from the evening hours when prices are high is to the best of our knowledge a new result,” the authors write. “It holds great promise for pricing strategies to improve economic efficiency in a transportation system reliant on electric vehicles.”
Alerting consumers to the real cost of their comfort makes them ask a pointed question with good implications for the economy and the environment: how much is my comfort worth to me?
As a marketing expert most interested in the impact of pricing on consumer behavior, Kopalle is at bottom a student of the consumer mindset. This experiment brought that fact to the fore, and reminded Kopalle of a line of research on the effect of pricing on the human brain. “I think our results here echo neuroscience literature saying that when people see a price, a particular part of the brain associated with decision making lights up and people feel like they’ve got to make a decision.” Inducing a condition known as “price primacy,” this literature shows that price-aware consumers shift their mindset from a qualitative focus (do I like it?) to a more value-oriented perspective (is it worth it?). Alerting consumers to the real cost of their comfort makes them ask a pointed question with good implications for the economy and the environment: how much is my comfort worth to me?