More and more, utilities are choosing demand response (DR) as a way to balance grid operations, lower energy prices for consumers, and integrate renewable resources like solar power.
Utilities have traditionally relied on large commercial customers to achieve those results. Yet residential customers represent a huge, untapped DR resource. The Federal Energy Regulatory Commission (FERC) estimates that utilities can deliver 65GW of peak reduction in the residential sector — equivalent to $3 billion worth of annual capacity.1
But, despite heavy investment, current residential DR programs engage less than 5% of homes2 and fall far short of FERC’s estimates of achievable potential.
How can utilities reach deeper into their service territories, engage the other 95% of homes, and unlock DR’s full potential? Leaders in the space are looking beyond existing models and employing solutions that take advantage of new customer-facing technologies, regulatory support for dynamic rates, and consumer adoption of connected devices. To reach deeper into their service territory and get the most out of their DR programs, utilities need to employ a comprehensive approach based on three key strategies:
1. Unlock the base through behavior: Engage up to 100% of customers through highly personalized, real-time communications
2. Keep dynamic pricing simple: Drive participation in dynamic pricing with simplified rate structures and engaging customer communications
3. Deepen customer relationships with connected devices: Encourage consumers to adopt connected thermostats through ongoing engagement and customer choice
This white paper will explore how leading utilities are reaching across their entire service territories to realize the full potential of their residential DR programs.
For most households, energy rates are static throughout the day and year, regardless of how much it actually costs utilities to generate that energy. As a result, there is little financial incentive for residential customers to engage in DR programs and reduce load during peak demand periods. In fact, just 5% of residential customers in the United States participate in DR programs, and only half know whether or not their utilities offer one.5,6 This is a huge opportunity for utilities — and not just from an operational perspective. Behavioral Demand Response (BDR) is a powerful tool to help utilities activate the other 95% of customers who aren’t currently engaged in DR to drive meaningful peak reduction at scale.
BDR uses billing and energy data analysis, applied behavioral science, and real-time, personalized, multi-channel communications to motivate customers to decrease usage when demand on the grid is highest. Prior to peak events, customers are notified through email or interactive voice response (IVR) and given timely, energy saving tips such as adjusting their thermostat and delaying the use of large appliances. After peak events, customers receive highly personalized feedback on how their usage compared to similar households. This positive feedback loop ensures customers are aware of the need for DR and continue to take steps to meet this need.
By leveraging utilities’ existing AMI investments, BDR can be deployed with ease and scale across the entire customer base without rolling a single truck or installing a single device. It unlocks previously untapped value as participants begin saving energy and money on their bills, and utilities start winning their trust. That trust then opens the door to the wider world of DR programs, like dynamic pricing and connected thermostats. Over time, utilities can move customers up the engagement pyramid by using rich analytics to promote programs to those who are most likely to benefit — deepening the utility customer relationship and unlocking greater savings for both. Just like Opower’s home energy reports did for energy efficiency, BDR is making residential peak load reduction a reality on a large scale.
Nationwide, regulators are increasingly supporting time-based rates for residential customers. The Massachusetts Department of Public Utilities recently announced that they will require time-of-use rates for every customer in the state.7 And, in the Mid-Atlantic, utilities have started rolling out large, opt-out, peak-time rebate programs for many of their customers.
However, many customers haven’t bought into dynamic pricing yet. It’s largely a consequence of education — these programs have often asked consumers to interpret complicated pricing tiers without much direction. As a result, less than 2% of U.S. residential customers are currently enrolled in any form of dynamic rate program today.8
Traditionally, utilities have built their residential DR programs around load control switches and thermostats. In exchange for installing these devices, customers see little benefit beyond small, annual incentive payments.
Connected thermostats are a game changer. Unlike other DR devices, consumer demand for advanced thermostats is high11 — and that gives utilities a huge new opportunity to deepen their engagement with customers.
That’s exactly what customers want. Studies show that people are 4x more likely to consider buying a connected thermostat (or other energy management services) from their utilities than from third parties.12
Rather than getting cut out of the equation by new entrants, utilities should seize this moment and get the most out of their residential DR programs. That means giving customers choice. The best connected thermostat strategies offer devices at a wide variety of price points through many delivery channels — including retail, professional installers, and direct utility install.
Utility-led connected device programs can deliver more than DR value. By providing customers year-round opportunities to save energy, utilities can also reduce the need for ongoing cash incentives.
This is a watershed moment for demand response. With the arrival of dynamic pricing, smart thermostats, and real-time analytics, utilities finally have the tools they need to get 100% of their customers thinking about peak demand. Additionally, the push for time-based rates and connected devices signals new opportunities for utilities to provide customers increased benefits through DR programs and strengthen customer relationships.
The untapped potential is huge. A 500,000–home utility that launches a behavioral DR program across its service territory stands to reduce peak demand by 156 MWs, save 43 GWhs, and start boosting customer engagement and satisfaction in a big way.
With demand response, utilities are poised to unlock the cheapest, cleanest, most abundant energy resource of all: their customers. And there has never been a better time to act.
1. The Brattle Group, May 16, 2007, “The Power of Five Percent, How Dynamic Pricing Can Save $35 Billion in Electricity Costs.” Available at: http://sites.energetics.com/madri/pdfs/ArticleReport2441.pdf. 65GW x $52/kW-year = $3 billion.
2. Federal Energy Regulatory Commission, December 2012, “Assessment of Demand Response and Advanced Metering Staff Report,” pg. 112. Available at: http://www.ferc.gov/legal/staff-reports/12-20-12-demand-response.pdf. 6 million customers on Direct Load Control. Roughly 115 million households per http://quickfacts.census.gov/qfd/states/00000.html.
3. Federal Energy Regulatory Commission, June 2009, “A National Assessment of Demand Response Potential,” pg. 29. Available at: http://www.ferc.gov/legal/staff-reports/06-09-demand-response.pdf.
4. Opower, Webinar, February 2014, “Solving the Dynamic Pricing Puzzle.” Available at: http://vimeo.com/84058078.
5. Parago, Infographic, June 16, 2014, “Turn up demand response: education and incent energy consumers.” Available at: http://www.parago.com/report/turn-up-demand-response-energy-infographic.
6. Energy Central, April 3, 2013, “Where are those time-of-use electricity rates?” Available at: http://electricity.providerpower.com/p/3999126359/2013/04/03/where-are-those-time-of-use-electricity-rates.
7. Massachusetts Department of Public Utilities, June 12, 2014. “Anticipated policy framework for time varying rates.” Available at: http://www.mass.gov/eea/docs/dpu/orders/d-p-u-14-04-b-order-6-12-14.pdf.
8. Faruqui, Ahmad; Intelligent Utility, April 1, 2014, “Study Ontario for TOU lessons.” Available at: http://www.intelligentutility.com/ article/14/04/study-ontario-tou-lessons.
9. Faruqui, Ahmad; Hledik, Ryan; Public Utilities Fortnightly, March 2009, “Transition to Dynamic Pricing, A step-by-step approach to intelligent rate design.” Available at: http://www.fortnightly.com/fortnightly/2009/03/transition dynamic-pricing.
10. (1) Sempra Energy; August 19, 2013, “Final Report – Peak Time Rebate Program Process Evaluation,” pp. 12-16. Available at: http://www.calmac.org/publications/Sempra_PTR_final_report_FINAL.pdf. (2) Baltimore Gas & Electric; November 15, 2013, “Quarterly Smart Grid Report,” Available at: http://220.127.116.11. (3) Braithwait, Stephen; Hansen, Daniel; Hilbrink, Maria; San Diego Gas & Electric, April 1, 2013, “2012 Load Impact of San Diego Gas & Electric’s Peak Time Rebate Program,” pg. 12. Available at: https://www.sdge.com/sites/default/files/regulatory/Draft Residential Peak Time Rebate Evaluation Program Year 2012.doc.
11. Markets and Markets, October 13, 2013, “Smart Homes Market – by Products.” Available at: http://www.marketsandmarkets.com/PressReleases/global-smart-homes-market.asp.
12. Gohn, Bob; Strother, Neil; Pike Research, 2012, “Home Energy Management.” Available at: http://www.navigantresearch.com/wp-content/uploads/2012/05/HEM-12-Final-Executive-Summary.pdf.
13. Benefit calculation assumptions: 4.0 kW average usage, 15,000 kWh average usage, $100.00/kW-year capacity, $0.05 / kWh avoided cost.