Note: This is the third part of an ongoing blog series about how an AMx framework can help energy utilities accelerate decarbonization.
As the electric grid shifts to more intermittent renewable generation amidst rapid load growth (due both to AI-driven loads and to growing electrification efforts), and as the gas system sees emerging demand and supply changes—and possibly even future distribution system decommissioning—load flexibility is emerging as a critical non-wires and non-pipeline alternative (NWA or NPA) that can help meet reliability needs while keeping costs as low as possible. To meet these challenges, electric and gas utilities will need to expand beyond their current offerings, and behavioral load management strategies supported by an AMx framework (which allows utilities to access more granular, timely data from existing meters) represent an especially promising approach to scaling up load flexibility while also bolstering existing offerings.
Behavioral load management essentially involves engaging with customers and asking them to voluntarily change their energy consumption for a period of time, with or without incentives. Although behavioral demand response (BDR) programs designed to reduce peak demand have been around for roughly a decade, relatively few utilities currently offer these programs, often due to concerns about consistency of savings and a view that automated demand response (ADR) programs—like those using smart thermostats—offer more promise given their relatively large per-customer demand reductions. However, a number of recent pilots support the notion that BDR can offer significant demand reductions that are quantifiable, consistent, and scalable.
The demand reductions demonstrated in BDR events are typically smaller than those seen in smart thermostat ADR programs, but what makes them particularly compelling is the potential scale they can reach. Smart thermostats are currently in less than 20% of US homes, according to S&P Global Market Intelligence, limiting the maximum potential reach of thermostat-based ADR programs. This is particularly relevant considering that customer participation in demand response programs is often 10% or less of the target population. In contrast, BDR programs that aren’t reliant on in-home technology and are more fundamentally based on effective customer engagement have potential to be scaled widely across nearly an entire service territory, enabling deeper load impacts than thermostat-based approaches alone may be able to offer. Similarly, many low- to moderate-income customers don’t currently have reliable in-home Wi-Fi, making them effectively unable to participate in existing utility ADR programs (regardless of the cost of the thermostat or other supporting equipment). For this reason, BDR approaches that don’t require Wi-Fi can help utilities expand both the reach and equity of their load management programs.
BDR offerings can also help complement and support existing ADR programs by increasing customer engagement. For example, a number of thermostat-based demand response programs have unexpectedly made the news over the past few years as a result of customers who forgot they signed up and then got upset when their utility unexpectedly adjusted their thermostat, or as a result of mistrust about why utilities would want to promote smart thermostats. Better customer engagement, and an increased diversity of load management approaches, can help remind customers why they signed up in the first place and the value of their participation so that they are more likely to remain positive contributors to these programs.
For gas utilities in particular, load flexibility could represent a key NPA that can help ensure reliability and increase resilience in the face of more extreme climate-driven storms, adoption of new kinds of less energy-dense gaseous fuels like hydrogen, or new policies that could make it harder for gas utilities to replace pipes (or which even drive gas system decommissioning). While load flexibility and demand response will necessarily look different for gas utilities than they will for electric utilities, it’s an area rife with opportunity for increased exploration, and BDR strategies may be particularly beneficial in dealing with prolonged gas demand peaks (e.g. taking place over the course of a full day rather than just a few hours).
Regardless of the approach used to reduce demand, high-interval data like that provided through an AMx approach can also open the door to new incentive approaches for load flexibility, such as customized real-time incentives that reflect actual customer load impacts and benefits to the utility system for a given event. These kinds of performance-based incentives have potential to significantly improve average demand reductions and customer satisfaction compared to BDR programs that don’t include these kinds of meaningful feedback and incentives. If effectively optimized, data-driven BDR with timely performance-based rebates has potential to become a fundamentally more equitable and cost-effective way to run future load management programs.
In the next part of this blog series, we’ll explore how an AMx framework can uniquely support utility demand-side management and electrification programs while improving the customer experience. We hope you’ll join us!