Across the Americas, climate change is putting pressure on energy providers. To keep the lights on during extreme weather, from the hottest summers on record to frigid winters, many are turning to demand management programs.
These programs encourage households to reduce their energy use during peak hours through time-based rates and other forms of financial incentives. Undoubtedly, demand response is a valuable tool to keep energy grids more stable when they’re needed most. How can behavioral insights help?
Because behavior change is at the center of demand management—to shift household habits—a behavioral insights approach can point to many solutions. Here are three evidence-based ideas that energy planners, operators, and utilities can use to support the roll out of their next demand management program.
Change the default
Default options are one of the most powerful tools in behavioral science, and they’re relatively easy to implement. People tend to choose the default over alternatives, especially when presented with complex information.
This can have major consequences for demand management programs, as they need many households to participate in order to be effective. Whether such a program is designed to be opt-out rather than opt-in can have a big impact on engagement.
For example, BIT partnered with Powershop, an Australian electricity retailer, to increase the use of their Curb Your Power (CYP) demand response program. One strategy we used was changing the default.
Powershop customers who were not in CYP were defaulted into the program, but given the option to opt out. In our trial, the households who were automatically enrolled in the program by default used an impressive 13.8% less power during peak times.
Automation is a tool that can complement defaults, ensuring it’s as easy as possible for households to participate in demand management programs and save energy. In the UK, we ran a randomized controlled trial to test whether a learning thermostat is more effective than conventional heating controls.
Conventional heating controls can be hard for people to set up and operate correctly. A learning thermostat, such as a Nest, uses sensors and machine learning to continually analyze home temperatures and occupancy habits, and tweak heating accordingly.
We found that Nest thermostats saved around 6-7% of the heating system’s gas use, with no loss of user comfort. Together, defaults and automation can significantly affect the success of a demand management program.
Frame your message carefully
How a message is presented or framed affects how people interpret it and what they consider to be relevant facts. In behavioral science, this is called framing effects.
Framing effects is an important concept for energy planners, operators, and utilities to consider when communicating about demand management programs to households. For example, behavioral insights tell us that we’re more influenced by losing something than we are by equivalent gains—a bias called loss aversion.
Therefore, households will more heavily consider the costs versus the benefits of demand response. Likewise, there are motivations and barriers (other than financial ones) that providers should consider when framing a message.
BIT recently worked with Gumtree, one of the UK’s largest websites for classifieds, to investigate if framing effects can encourage people to buy second-hand. We found that making the environmental and financial benefits of buying second-hand more prominent helped encourage more purchasing through the website.
This insight is straightforward, but worth mentioning. Messaging and framing are too often overlooked when communicating about technical or complex issues, such as demand response. We see a big opportunity here for energy providers.
Consider the community’s social norms
People are social by nature. What we see and hear about other people doing affects our own actions. By better understanding social norms—the unwritten rules governing behavior in groups and society—we can design more effective programs.
This behavioral insight is particularly important for demand management because in order to be effective, broad community participation is required. Leveraging defaults and social norms can help achieve this.
Researchers from the University of Vermont analyzed the impact of a demand response program informed by pro-social behavior (i.e., it highlighted how individual consumer’s energy habits can benefit the entire community). Over 16,000 households in Burlington, VT participated and they found that the program, which was designed to encourage social and collective action from the community, achieved a 13.5% decrease in energy use during an annual peak event with a return on investment of 11 to 1 for the utility.
There’s no question, we will face more extreme weather events in the future, even as countries make progress on climate change goals. That means demand management programs will continue to grow. Defaults, framing effects, and social norms are just three insights among many from behavioral science that can support their success.
To learn more about how we can apply behavioral insights to your demand management program, please contact Marcos Pelenur.