Convincing Consumers to Adopt Dynamic Electricity Pricing
If utilities offer sign-up incentives they can attract the right customers.
Every few days I get a mailer from a bank or credit card company enticing me to sign-up for their product with an offer of a cash bonus or airline miles. The constant flow of this mail shows that banks think it’s a good strategy to get consumers to sign up. Recently published research by Koichiro Ito, Takanori Ida and Makoto Tanaka finds that offering up-front incentives can also be an effective strategy for energy policymakers.
The authors conducted a randomized field experiment that offered households a bonus if they signed up for a dynamic electricity pricing plan. They found that, not surprisingly, the incentive increased sign-ups. But what was really powerful about the incentive, and not obvious, was that the right amount of incentive can attract the households that policymakers most want and, moreover, these incentives can be tailored to different customer types to further increase benefits.
More Frequent Price Swings
Most US electricity consumers pay the same price for each unit of electricity they use, whatever the time. Many California consumers recently moved to a time-of-use rate that increases every afternoon between 4 and 9pm. However, the costs to produce electricity can swing up and down from one hour to the next and jump to very high levels on the few days when the grid is strained. Utilities have to absorb these costs, which are reflected in wholesale market prices, in order to offer the flat or time-of-use price to consumers. At times this means purchasing expensive electricity generated by inefficient power plants that are expensive to operate. Consumers are unaware of how high the true costs are because they get to pay the usual rate.
The swings in wholesale market prices are large. In the California Independent System Operator’s area in 2022, one percent of the time prices exceeded $250 per megawatt-hour (five times the average noon price), sometimes exceeding $1,000 per megawatt-hour (20 times the average noon price). Prices swung negative too, about one percent of the time. When prices are negative, wind and solar power plants may shut down, undermining the economics of these carbon free energy sources. The frequency of really high prices and negative prices increased in 2022 relative to the year before. As more wind and solar energy join the grid and electricity demand is buffeted by climate change-driven weather events, extreme prices could become even more common.
A powerful policy response, such as dynamic electricity pricing, could reduce these wholesale price fluctuations. These plans provide consumers an opportunity to save money by decreasing their use when electricity prices are high and increasing their use when prices are low or negative. Economists have long advocated for dynamic pricing because it better aligns demand with supply.
California policymakers are moving in this direction. The California Energy Commission (CEC) has adopted standards that require electricity providers to offer dynamic pricing as an option to all of their consumers by 2027. Later this month, the California Public Utilities Commission will consider a policy that would significantly expand dynamic pricing pilots for the state’s two largest utilities, a step toward meeting the CEC’s goals. This new research into consumer incentives comes at the right time to be rolled into the pilots and increase adoption.
Setting and Targeting Incentives
Ito, Ida and Tanaka note that policymakers have typically not required consumers to switch to dynamic electricity pricing. Instead, policymakers have approved programs that require consumers to proactively join. In the experiment, some consumers were offered an incentive to encourage sign-up. Others were not.
The authors found that a sign-up incentive increased the voluntary take-up rate from around 30% to almost 50%. They then analyzed what sorts of customers were encouraged by the incentive. The value of dynamic pricing programs comes from attracting consumers who will change their electricity usage in response to price changes. A program that hands out lots of incentives to customers that do not make any meaningful changes is expensive for the government to run and provides little benefit.
The researchers found that the households enticed by the incentive indeed were the ones that respond to the price changes. Many of these consumers were at risk of seeing higher bills on the dynamic pricing rate, but the incentive convinced them to sign on. The incentive offset the possible loss. The opportunity to change their demand could make them clear winners. The additional households also included ones that were relatively more nervous about giving up the certainty of their traditional flat rate. The incentive was enough to convince them to take a chance with the new rate.
But how high should sign-up incentives be set? Higher incentives attract even more households. However, the research demonstrates there is a downside to setting the incentive too high. If the sign-up incentive is ratcheted up, the additional households that join are less responsive to the dynamic prices than the households that join at a lower incentive level. Also, among the costs of signing up for a new pricing plan is the effort of going through the switching process and the ongoing attention a household needs to devote to managing electricity usage. When I’ve received offers of a cash reward to open a new bank account my mind goes to these costs – all the sign-up forms, learning how to use a new website, etc…Setting a really high sign-up incentive can lure consumers who are more likely to get frustrated with the burden.
As with most papers that study a specific program (in this case a program in Japan) the research doesn’t give policymakers and utilities everywhere a precise dollar number incentive that should be used in every instance. But it does provide guidance for how to think about the decision.
The authors also provide some very implementable results on the value of targeting an incentive. Their analysis shows how easy-to-get data about households, such as historical electricity use, can be used to set targeted incentive levels and increase benefits. In California, I would suggest policymakers consider climate zones too. This research adds to a robust set of studies on how to design and roll out peak electricity pricing. This includes research addressing how to set the peak and off-peak prices, when to trigger peak pricing and the significant benefits of using an opt-out design (as opposed to an opt-in design). With more peaks and troughs coming to the grid every year, it’s time for utilities and policymakers to put these lessons into practice.
Follow us on Bluesky and LinkedIn, as well as subscribe to our email list to keep up with future content and announcements.
Suggested citation: Campbell, Andrew. “Convincing Consumers to Adopt Dynamic Electricity Pricing” Energy Institute Blog, UC Berkeley, January 16, 2024, https://energyathaas.wordpress.com/2024/01/16/convincing-consumers-to-adopt-dynamic-electricity-pricing/
Categories
Andrew G Campbell View All
Andrew Campbell is the Executive Director of the Energy Institute at Haas at the University of California, Berkeley. At the Energy Institute, Campbell serves as a bridge between the research community, and business and policy leaders on energy economics and policy.
Energy Institute Blog 
FlbrkMike you certainly have a complex system. I agree that 99% of residential consumers will want systems that made decisions for them. Even sophisticated consumers like yourself probably don’t benefit by monitoring real time prices every hour in order to save an additional $$ a few times a week.
But there is a convenient approach that makes you better off under RTP without requiring your active involvement. Simply assume that the expected value of prices will happen for sure, and automate responding to those prices as if they are TOU. Behavior will probably be very similar to what you do now. Then on top of this, get an alert when prices are anticipated to go exceptionally high — roughly 3 to 10 days in August-October. On those occasions only, manually alter your plan for the next 24 hours. Those 10 episodes will give big $ savings, at the cost of only a little of your time.
With modern tools, it would also be easy to create a company to advise customers like you via text messages. (It’s not quite as simple as I describe, but I’d have to reread some 30 year old papers to remember the details.) It’s hard to calculate “optimal” behavior under RTP, but easy to get results that are better than under TOU.
Roger
You just described Critical Peak Period (CPP) pricing with TOU rates. California’s IOUs already have this program, but it has very low residential enrollment. There’s really no need for the expense of RTP rates infrastructure if we think the CPP is sufficient for 99% of the customers.