Despite billions of dollars invested in advanced metering infrastructure (AMI), new ACEEE research finds that most utilities have vastly underused this technology to help customers save energy.
The report, which surveys 52 of the largest US electric utilities, shows how utilities can tap such data to deliver energy savings.
Big data, big savings:
We live in an age of “big data.” Our digital and connected world creates, transmits, and stores immense amounts of data on all aspects of our lives. Not surprisingly, AMI — which comprises smart meters, communication networks, and data management systems — has grown rapidly. A key element of grid modernization, AMI is now in place in many states, covering nearly half of all meters in the United States.
AMI measures our electricity use in short intervals (typically 15 minutes or 60 minutes) rather than by month. Our electricity providers can use such timely, granular data to better manage and optimize generation and grid operations, thereby reducing costs and responding faster to power outages. They can also use the data to offer better programs and share insights from the data to encourage customers to save energy.
Yet our report shows that only one of the 52 utilities surveyed — Portland General Electric (PGE) — is building its capacity to optimise use of AMI for saving energy. PGE is tapping all six of the use cases we have identified for applying the data. These cases fall into four categories:
- Feedback: Moving from monthly, confusing energy bills to near real-time, customized feedback and applying behavioural insights on how customers can save energy and money.
- Pricing: Shifting from fixed rates that don’t reflect the underlying cost of service to time-of-use rates that inform and enable customers to respond to price signals.
- Data disaggregation: Using granular data for program targeting, evaluation, and innovative designs, such as “pay-for-performance.”
- Grid connectivity: Offering new programs with grid value and customer bill savings, such as grid-interactive efficient buildings (GEB) and conservation voltage reduction.
Our survey showed that behaviour-based feedback and time-of-use rates are the most prevalent use cases, with 26 utilities implementing each of these measures. The least common are newer applications: data disaggregation (seven utilities) and GEBs (four utilities).
PGE has developed customer applications for AMI data, which include customer portals to track near-real-time energy use, data disaggregation for key end uses, behavioural tools, connections to energy efficiency programs, and pricing alerts. It is also piloting time-varying rates and conservation voltage-reduction programs.
Three utilities in our data set, Commonwealth Edison, NV Energy, and CPS Energy, leverage AMI for five use cases. Twenty-one utilities leverage AMI for two to four use cases, and seven report using AMI for only one use case.
These findings suggest a large untapped potential for using AMI to deliver energy savings.
AMI needs to be paired with other tools
We found that providing customers with AMI data alone generally does not result in energy savings. Rather, the data should be paired with customer engagement tools, pricing and incentive strategies, and programs that enable, motivate, and support customers to take actions to modify their energy use.
For example, Baltimore Gas and Electric automatically enrolls customers in its Smart Energy Rewards program when AMI is installed. Customers receive feedback, peak time rebate incentives, and corresponding information on programs to reduce energy costs from energy efficiency and demand response measures.
Targeting programs to customers most likely to benefit from them is another way to leverage AMI. As an example, Pacific Gas & Electric found that AMI-based targeting for a home retrofit program could deliver 3.5 times more energy savings in targeted homes than in non-targeted ones.
Failure to optimise AMI’s potential for customer energy and cost savings can pose risks to utilities because these benefits are typically used to justify AMI investments. Regulators could deny cost recovery of such investments or not approve future investments proposed by utilities. There are cases of such regulatory rejections of AMI in Massachusetts, Kentucky, Virginia, and New Mexico.
How to optimise AMI’s potential:
To optimise AMI’s potential for energy savings, utilities may need to overcome regulatory, technological, and structural barriers and take steps to invest in complementary systems and workforce, prioritise the customer experience, and pilot new approaches and ways of leveraging the data.
Utilities will need the support of their regulators. For their part, regulators will need to recognize, support, and promote the energy-saving benefits of AMI in investment approval and oversight. In many cases, they will need to establish protocols for data access. They can consider creating performance incentives to encourage use of AMI for energy savings and can also encourage new uses of AMI data through innovation and pilots.
AMI is part of the fundamental transformation underway in our electric utility system. We are rapidly moving from a system marked by large, centralized resources with one-way flows of energy and information to an advanced grid marked by distributed, decentralized, decarbonized resources with two-way flows of energy and information. Greater energy efficiency and flexible loads will be hallmarks of an advanced grid. Our research shows how AMI is a powerful tool for helping customers and utilities manage and reduce their energy use and costs, benefitting both. Most utilities do not currently capture these benefits and should take steps to maximize AMI to save energy.
A slightly different version of the story first appeared on ACEEE.org
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