AMI 2.0
February 2026
9 / 9
Overview
Advanced Metering Infrastructure (AMI), or Smart Meters, are energy metering devices that collect data from end-users’ devices and measure their energy consumption in real-time[1]. This data is then transmitted to the utility company and/or system operator, providing superior quality information for grid operations and system planning. AMI 2.0 incorporates multiple sensors and control devices, supported by a dedicated communication infrastructure, to facilitate real-time data acquisition and transmission[2].
Benefits
Inverter-Based Systems Integration
AMI 2.0 facilitates the integration of inverter-based distributed energy resources by providing data on energy usage and generation, supporting better management and coordination within the grid. While using AMI as a communication medium to directly control inverters is still in early pilot and feasibility stages, AMI does leverage production meter demand data—typically collected every 5 to 15 minutes for DER accounts. This data can trigger DERMS software to automatically perform control actions, such as dispatching inverter excess demand capacity to the grid. However, the actual communication between the DERMS system and the inverter for data acquisition and control is typically achieved through cellular networks or the end-customer’s Ethernet/Internet connection[3].
Outage Mitigation
AMI 2.0 improves restoration efforts by providing real-time information on outages and consumption patterns, enabling faster responses to faults and better situational awareness for utility operators.
Improved Grid Stability
By offering real-time monitoring and data analytics, AMI 2.0 contributes to maintaining grid stability, allowing for quick detection of anomalies and more effective responses to fluctuations. However, achieving this level of insight requires significant big data processing, assuming AMI 2.0 smart meters are deployed at the customer level to capture such detailed information. In practice, utilities have often found that placing Phasor Measurement Units (PMUs) at strategic locations throughout the system can be a more cost-effective approach to achieving similar visibility into grid conditions.
Enhanced Grid Analytics
AMI provides near-real-time demand analytics at the feeder level for improved asset management of transformers and for defined virtual meter groups. This feeder demand data is typically fed into the utility’s Meter Data Management System.
Power Quality and Locational Awareness
AMI 2.0 systems provide wavelength power sampling and can send alarms or reports to headend systems when specific meters fall outside of power quality thresholds. AMI 2.0 can also enhance data quality by continuously improving GIS data to better align meter-to-transformer and meter-to-phase relationships, which supports a wide range of grid modernization use cases[4]. However, this functionality can be limited for some utilities due to challenges with data integrity in system representation. Specifically, it requires detailed modeling of the secondary network beyond the step-down transformer at the distribution level. A common issue is customer-to-transformer error association, which can hinder the accuracy and effectiveness of locational awareness efforts.
Enhanced Demand Response over AMI
While AMI 1.0 offers direct load control, AMI 2.0 enhances this with emerging use cases such as shifting EV charging to lower demand times for participating subscribers and additional load control opportunities.While AMI 1.0 offers direct load control, AMI 2.0 enhances this with emerging use cases such as shifting EV charging to lower demand times for participating subscribers and additional load control opportunities.
Technology Readiness Level (TRL)
- System proven in real operations
- Full range of operating conditions
- Deployed in production environment
- Fully mature technology
Meters, sensors, and communication infrastructure to support AMI 2.0 exist on the commercial market.
Adoption Readiness Level (ARL)
Value Proposition
Delivered Cost
Low Risk
The life cycle cost of AMI 2.0 shows cost advantages compared to conventional meters. Also, the life cycle cost of AMI 2.0 is approximately 50–100% higher than AMI 1.0, due to greater sophistication of the meter and 10–15 years of inflationary increases. The competition among AMI vendors offers a competitive landscape and drives continuous product improvements.
The introduction of multi-carrier cellular and private LTE in the meter allows for high connectivity and smart sensor improvements of 100–200% over AMI 1.0, as well as reduced latency[5]. While meter and communication costs are higher with AMI 2.0, performance improvements open new grid modernization use cases that were not possible with AMI 1.0. Recent trends for utilities developing their own private LTE networks and/or AMI vendors offering cellular in the meter with fail-over to two or more cell carriers further improve reliability while offering utilities options to discontinue provider services while centralizing communications networks.
The hardware cost of AMI 2.0 is slightly higher, with some sources estimating costs between two and four times higher than traditional meters (analog or digital).
Next-generation AMI technologies—such as high-frequency voltage data streams and edge analytics—are already enabling a range of operational improvements in electric utilities. Demonstrated on real U.S. distribution feeders by the National Laboratory of the Rockies (NLR), these capabilities support use cases like phase identification, secondary-voltage monitoring, and integration with Advanced Distribution Management Systems (ADMS)[6].
In practical terms, these applications translate into measurable operational efficiencies: fewer field service visits (avoided truck rolls), faster power restoration following outages, and improved accuracy in system planning models.
From an economic standpoint, while the upfront hardware cost of smart meters is higher—typically ranging from $200 to $500 per unit compared to $50 to $300 for conventional analog or digital meters—their life cycle cost profile often proves more favorable[7]. This is due to the long-term operational savings and enhanced system performance they enable. When accounting for avoided labor costs, reduced outage durations, and improved asset utilization, smart meters can offer a net economic benefit over their lifespan.
Functionality Performance
Low Risk
High accuracy and real-time data capabilities suggest a high level of maturity in the technology. Enhanced outage management and restoration efficiency are key performance indicators for AMI 2.0. Effective integration with variable energy sources and grid stability support indicates advanced functionality.
The transition to AMI 2.0 primarily involves layering advanced software capabilities and targeted communications upgrades onto an already extensive infrastructure—over 70% of U.S. households are currently equipped with first-generation AMI systems[8]. As a result, the incremental capital expenditure (CAPEX) required for this next phase is relatively modest compared to the initial wave of deployments. It is important to note that the economic value of AMI 2.0 stems not from large-scale physical infrastructure investments (e.g., new poles and wires), but from the enhanced analytics and data-driven functionalities it enables.
The high accuracy and real-time data capabilities of AMI 2.0 reflect a mature technological platform. Key performance indicators include improved outage detection and restoration efficiency, which reduce service disruption costs and enhance customer satisfaction. Furthermore, the ability to effectively integrate distributed energy resources and support grid stability highlights the advanced operational functionality of these systems.
From an economic perspective, these improvements contribute to more efficient grid management, reduced operational costs, and better-informed investment planning, delivering long-term value to utilities and ratepayers alike.
Ease of Use/Complexity
Medium Risk
User-friendly interfaces allow consumers to monitor real-time energy usage and manage their consumption.
Remote operation of the meter does not require technicians to physically visit the meter outside of installation and physical maintenance. Some additional installation training is required for technicians but does not pose a significant barrier.
The operational switching costs associated with AMI 2.0 are relatively moderate, primarily because the upgrade builds upon existing infrastructure, including meters, head-end systems, and Meter Data Management Systems (MDMS). Rather than requiring extensive field-based infrastructure replacements, the primary effort lies in integrating new data streams and developing analytics workflows.
Demonstrations conducted by the DOE and NRL have shown that AMI data can be effectively integrated into Advanced Distribution Management System (ADMS) applications, such as volt/VAR optimization and phase identification. These demonstrations outline clear integration steps and highlight workforce implications, particularly in the areas of data engineering and operations. Note that the transition requires relatively limited retraining compared to greenfield system deployments.
The more nuanced challenges are technical in nature—centered on data quality, sampling frequency, and alignment between AMI data and grid models. While these issues have been documented in laboratory settings, they are generally manageable within the scope of standard utility processes and do not present insurmountable barriers to implementation.
Market Acceptance
Demand Maturity/Market Openness
Low Risk
Significant investments by utilities in smart metering technology have occurred, indicating readiness and commitment to the technology. Increasing consumer awareness and acceptance of AMI 2.0 and its benefits is leading to a more positive view of the transition. Adoption in many regions, particularly in developed countries, indicates high demand maturity.
Utilities are increasingly seeking ways to enhance service reliability and billing accuracy. Smart meters offer a foundation for achieving these goals by enabling operational improvements that can reduce outage frequency and duration, while also supporting more precise and transparent billing practices.
Evidence from the U.S. Department of Energy’s Voices of Experience initiative indicates that utilities are moving beyond the initial use case of remote meter reading[9]. Instead, they are leveraging AMI networks and data to support grid operations and customer-facing programs. This evolution enhances the credibility—or “bankability”—of analytics-driven use cases, making them more attractive for internal investment and external financing.
Furthermore, federal programs such as DOE’s Grid Resilience and Innovation Partnerships (GRIP) and Smart Grid Investment Grant initiatives provide public co-funding that helps de-risk adoption. By offsetting upfront costs and validating new technologies, these programs lower the perceived financial and operational risks associated with AMI 2.0 deployment[10].
Market Size
Medium Risk
Nearly 120 million smart meters have been installed across the United States, with the infrastructure in place to potentially serve up to 145 million customers. Projections indicate that smart meter adoption could reach approximately 93% of all U.S. electricity customers between 2021 and 2027, signaling a near-universal transition to advanced metering technologies[11].
However, the pace and extent of smart meter deployment vary significantly by region and customer class (e.g., residential, commercial, industrial). These differences are largely influenced by state-level regulatory approvals and the timing of individual utility investment cycles. As a result, while national penetration rates are rising, the realization of full AMI functionality remains uneven and contingent on local policy and utility-specific planning horizons.
Downstream Value Chain
Low Risk
Established manufacturers with robust supply chains ensure consistent quality and supply of smart meters. Professional services for installation and integration are widely available, supporting efficient deployment.
The AMI 2.0 ecosystem benefits from established manufacturers with robust, global supply chains that ensure consistent product quality and reliable delivery. This industrial maturity reduces procurement risk and supports large-scale deployments. In parallel, a well-developed market for professional services—including installation, systems integration, and commissioning—facilitates efficient and timely implementation.
AMI 2.0 advances through a mature, utility-centered value chain that spans from meter and hardware vendors, through head-end systems and MDMS, to utility operations and customer-facing programs. This structure leverages well-established procurement and integration pathways. Evidence from the U.S. Department of Energy’s Smart Grid Investment Grant (SGIG) program demonstrates that large-scale AMI rollouts have been successfully executed using standard utility contracting mechanisms and integration practices, underscoring the sector’s readiness for continued expansion.
Resource Maturity
Capital Flow
Low Risk
Investment from both public and private sectors is driving the development and deployment of AMI 2.0. Utilities are making large-scale investments in metering infrastructure and related technologies. Favorable cost-benefit analyses support continued investment in AMI 2.0 technology.
The development and deployment of smart meter technologies are being fueled by substantial investment from both public and private sectors. Utilities across the U.S. are committing capital to modernize metering infrastructure and associated digital systems. These investments are underpinned by favorable cost-benefit analyses, which consistently demonstrate the long-term economic and operational value of AMI technologies.
Federal cost-sharing has played a pivotal role in accelerating adoption. The U.S. Department of Energy’s Grid Resilience and Innovation Partnerships (GRIP) program allocates $10.5 billion toward grid modernization, with $7.6 billion already awarded in the first two funding rounds. This disbursement of capital reflects strong federal commitment and provides support for utility-led digital infrastructure upgrades, including AMI 2.0 and advanced analytics platforms[10].
Historical precedent further reinforces investor confidence. The Smart Grid Investment Grant (SGIG) program (2010–2015) deployed $3.4 billion in federal funding, catalyzing billions more in private-sector co-investment. The program successfully completed 99 projects, establishing replicable models for benefit-cost analysis, procurement, and regulatory recovery—effectively lowering financing barriers for current AMI refresh cycles.
Moreover, regulatory processes for AMI deployment are now well-documented, as highlighted in DOE’s Voices of Experience initiative[9]. This institutional knowledge base enables more efficient alignment between utilities and public utility commissions, facilitating timely cost-recovery approvals and accelerating capital flow into grid modernization efforts.
Project Development, Integration, and Management
Low Risk
Utilities and technology providers in the U.S. possess extensive experience and technical expertise in executing large-scale smart meter deployments. This institutional knowledge base significantly reduces project risk and enhances implementation efficiency.
Deployment methodologies are well-established and have been validated at scale. The Smart Grid Investment Grant (SGIG) program synthesized lessons learned from numerous AMI rollouts, covering critical areas such as project planning, vendor coordination, installation logistics, and organizational change management[12]. These insights have been codified into repeatable playbooks that many utilities continue to follow today.
For system integration, resources such as DOE’s Voices of Experience initiative and technical documentation from NLR provide detailed guidance on incorporating AMI data into operational platforms. These include Advanced Distribution Management Systems (ADMS), Outage Management Systems (OMS), phase identification tools, and secondary-voltage monitoring applications. These resources clearly delineate roles across IT/OT teams, data engineering, and utility operations, helping to contain and predict execution risks.
Infrastructure
Low Risk
A diverse set of communication technologies—such as RF mesh, cellular, and power line communication—ensures that smart meter capabilities are broadly accessible across different utility environments. The widespread market penetration of AMI to date demonstrates that infrastructure constraints are not a critical barrier to deployment. Utilities have successfully implemented smart metering systems across urban, suburban, and rural contexts, indicating the adaptability and scalability of available communication solutions.
Further reinforcing this readiness, national laboratory initiatives have established AMI-based operational tool chains, including ADMS test beds and AMI-for-Operations platforms. These projects have demonstrated the feasibility of integrating smart meter data into real-time grid operations. In addition, national labs have published utility-facing methodologies for model calibration and parameter estimation using AMI data—providing practical tools and workflows that utilities can adopt.
Manufacturing and Supply Chain
Low Risk
While recent supply chain disruptions—due to the COVID-19 pandemic—have caused delays in smart meter deployments, these challenges are not unique to AMI and reflect broader pressures on advanced manufacturing sectors. Despite these temporary constraints, the underlying manufacturing and integration capabilities for AMI remain robust and well-established.
To date, U.S. utilities have installed approximately 119 million AMI meters, representing about 72% of all electric meters nationwide. This scale of deployment demonstrates the strength of vendor capacity and the repeatability of logistics and integration processes. The U.S. Department of Energy’s Smart Grid Investment Grant (SGIG) program previously supported 99 smart grid projects, establishing standardized playbooks for planning, procurement, and deployment that utilities continue to rely on[12].
Looking forward, the DOE’s Grid Resilience and Innovation Partnerships (GRIP) program provides substantial funding to support near-term AMI procurements and integration workstreams.
Materials Sourcing
Low Risk
Smart meter production benefits from the involvement of major global electronics manufacturers, many of which operate extensive and diversified supply chain networks. These networks enhance resilience by enabling flexible sourcing of key components and materials.
AMI 2.0 hardware primarily relies on widely used semiconductor technologies—such as system-on-chip (SoC) processors and communications chipsets—as well as lithium-based cells for backup and ancillary functions. As a result, material sourcing risks for AMI hardware align with broader trends in the global electronics and battery supply chains, rather than being driven by any AMI-specific dependency on rare earth elements or exotic materials.
The DOE has identified semiconductors as a keystone component in its supply chain assessments, noting their globally integrated production and strategic importance. In parallel, DOE’s National Blueprint for Lithium Batteries and Critical Materials Assessment outline ongoing federal actions to strengthen domestic supply chains for batteries and critical materials. These efforts aim to reduce systemic vulnerabilities and enhance long-term supply security.
In summary, while supply chain risks are real—particularly in the context of semiconductors and lithium—they are systemic to the broader electronics and battery sectors, not unique to AMI.
Workforce
Low Risk
Existing technicians can be trained to remove old meters and replace them with newer meters with AMI 2.0 capabilities.
The workforce required for smart meter deployment overlaps with the existing pool of skilled utility technicians responsible for installing and maintaining traditional meters. These personnel can be readily trained to remove legacy meters and install AMI devices, minimizing the need for specialized labor.
AMI 2.0 deployments typically leverage existing utility protection and operations staff, supplemented by data engineering support. This represents an incremental shift in workforce composition rather than a wholesale transformation. National laboratory demonstrations have shown that integrating AMI data into operational systems—such as Advanced Distribution Management Systems (ADMS) and Outage Management Systems (OMS)—can be achieved using current utility structures, with clearly defined roles for IT/OT coordination and data workflows.
License to Operate
Regulatory Environment
Low Risk
The regulatory framework governing utility deployment of smart meters remains consistent with existing oversight structures. Regulation for utilities using existing smart meters does not change with AMI 2.0.
The Federal Energy Regulatory Commission (FERC) and state public utility commissions (PUCs) continue to serve as the primary regulatory bodies overseeing AMI implementation. Utilities pursuing smart meter upgrades operate within established regulatory pathways, and no fundamental changes to utility regulation are required solely due to AMI adoption.
AMI 2.0 primarily impacts retail electricity customers, which are the purview of state regulatory bodies.
AMI is a mature, commission-approved utility asset class, with well-documented regulatory precedents established through the U.S. Department of Energy’s Smart Grid Investment Grant (SGIG) program and the Voices of Experience initiative. These efforts have helped standardize regulatory expectations and streamline approval processes.
While interoperability and cybersecurity remain active areas of regulatory attention, they are not novel challenges. These topics are explicitly addressed in DOE smart grid guidance and reporting, providing utilities with clear compliance frameworks.
Policy Environment
Low Risk
Supportive federal and state policies have created a favorable environment for the continued deployment and integration of smart meter technologies, contributing to a low-risk investment landscape. Legislative frameworks such as the Energy Policy Acts have explicitly encouraged the adoption of smart grid technologies—including AMI—by promoting improved electricity reliability, operational efficiency, and customer engagement. These policies have also provided direct funding mechanisms to accelerate deployment.
At the federal level, policy support is substantial. The U.S. Department of Energy’s Grid Resilience and Innovation Partnerships (GRIP) program administers $10.5 billion in funding for grid modernization, with multibillion-dollar allocations already announced. These investments actively support AMI upgrades, advanced analytics, and communications infrastructure, integrating them into broader utility modernization portfolios[10].
Historical experience from the Smart Grid Investment Grant (SGIG) program further reinforces policy stability. SGIG demonstrated consistent federal commitment to cost-sharing, transparent reporting, and performance tracking, establishing a precedent that reduces uncertainty for utilities and investors considering AMI 2.0 deployments today.
Permitting & Siting
Low Risk
AMI 2.0 is typically owned and installed by the utility company as part of the service offered to customers. If installation goes beyond the meter itself, local regulations may require some form of building permit.
Smart meters are typically owned and installed by the utility as part of the standard service provided to customers. In most cases, installation is limited to replacing the existing meter at the customer’s premises, which does not require structural modifications. However, if installation activities extend beyond the meter socket—such as upgrades to customer-owned infrastructure—local regulations may require building permits or inspections.
AMI 2.0 deployments are designed to minimize such complications. The technology is installed using existing meter sockets and leverages pre-established communications infrastructure, eliminating the need for new physical siting or major construction. As documented in the U.S. Department of Energy’s Smart Grid Investment Grant (SGIG) program, large-scale meter rollouts have been successfully executed using standard utility scheduling and customer notification procedures[12]. These processes are administrative in nature and do not typically trigger land-use or zoning reviews, keeping permitting risks low and deployment timelines predictable.
Environmental & Safety
Low Risk
Smart meters, including those deployed under AMI 2.0 initiatives, are subject to the same environmental and safety standards as traditional meters and must comply with all applicable local codes and regulations. From an environmental standpoint, the footprint of AMI deployment is minimal. Installations typically involve one-for-one device replacements at existing meter sockets, with no need for new infrastructure corridors or significant physical alterations.
Safety risks associated with AMI 2.0 are primarily digital rather than physical. The dominant concerns relate to data privacy and cybersecurity, rather than electrical or structural hazards. The U.S. Department of Energy’s Office of Cybersecurity, Energy Security, and Emergency Response (CESER) provides sector-specific guidance and baseline standards for securing distribution systems and edge devices, including those that interface with distributed energy resources (DERs) and meter networks.
Overall, the net externalities of AMI 2.0 are favorable. Enhanced operational capabilities enabled by smart meters contribute to faster outage detection and restoration and support advanced analytics for wildfire mitigation, both of which reduce community-level risk and improve system resilience.
Community Perception
Medium Risk
While smart meters have been widely adopted—over 120 million installed across the U.S.—some community opposition persists. Common concerns include data privacy, cybersecurity, and the perception that smart meters may lead to higher electricity bills. These concerns, though not universal, underscore the importance of transparent communication and thoughtful system design.
Importantly, privacy and public acceptance are manageable within existing regulatory and operational frameworks. The U.S. Department of Energy’s DataGuard initiative offers a voluntary code of conduct that provides utilities with a recognized framework for protecting consumer data privacy[13]. This framework helps build trust and demonstrates a commitment to responsible data stewardship.
As more utility transition to a time of use model the improved information from smart meters may work to further diminish opposition as customers see potential for user-driven bill decreases from changes in behavior. Privacy concerns would still exist.
Moreover, empirical evidence from Lawrence Berkeley National Laboratory’s Consumer Behavior Studies shows that customer engagement and satisfaction increase when smart meter deployments are paired with enabling technologies (e.g., in-home displays and time-of-use pricing) and clear, proactive communication strategies[14].
Case Studies & Implementation
Study of Smart Meter System Deployment
The Division of Ratepayer Advocates, an independent division within the California Public Utilities Commission (CPUC), published a study on Southern California Edison’s smart meter program. The CPUC DRA case study, published in 2012, focuses on the SmartConnect smart meter program. The report highlights how AMI automates energy usage data collection and replaces manual meter reads, enabling more detailed interval data and operational efficiencies. This report also underscores the challenges of tracking and realizing the projected costs and customer benefits, urging careful regulatory oversight to ensure that AMI investments deliver net value to ratepayers through improved billing operations, enhanced data availability, and potential customer savings.
https://docs.cpuc.ca.gov/PublishedDocs/EFILE/EXP/163180.PDF
Smart Grid & Smart Meters: The Results of Australia’s Trial
The Australian National Audit Office (ANAO) audited the administration of the Smart Grid, Smart City program. The Smart Grid, Smart City program is a government demonstration initiative aimed at deploying integrated smart grid technologies including smart meters, network innovations, and customer feedback systems to gather data and inform broader grid modernization. This report identifies the successful installations of many trial components, such as smart meters, grid-side applications, locally sourced energy generation integration tests, and electric vehicle trials. Additionally, this report describes challenges and recommended areas of improvement. The challenges include low customer participation in the retail tariff trial and responsibility complexities while the recommended areas of improvement entail better methods for performance reporting and additional support of achieving program objectives.
https://www.anao.gov.au/work/performance-audit/administration-the-smart-grid-smart-city-program
References
- IBM. What is Advanced Metering Infrasturcture (AMI)? Think. [Online] IBM, N.D. [Cited: February 3, 2026.] https://www.ibm.com/think/topics/advanced-metering-infrastructure.
- Deloitte. Enabling the clean energy transition: Planning for next-generation advanced metering infrastructure and grid technologies. Analysis. [Online] Deloitte, 2022. [Cited: February 3, 2026.] https://www.deloitte.com/us/en/Industries/energy/articles/next-gen-advanced-metering-infrastructure.html.
- Fehrenbacher, Ryan, et al. How utilities can prepare for the AMI 2.0. EY. [Online] EY, March 21, 2025. [Cited: February 3, 2026.] https://www.ey.com/en_us/insights/power-utilities/shape-smart-grid-future-with-next-gen-ami.
- Honeywell. A Data-Driven Approach to Adopting and Managing AMI 2.0. Houston : Honeywell, 2024.
- Janssen, Sascha and Petitgrand, Fabien. Harnessing the power of pLTE and AWS Cloud to optimize AMI 2.0 outcomes. AWS for Industries. [Online] AWS, May 15, 2025. [Cited: February 3, 2026.] https://aws.amazon.com/blogs/industries/harnessing-the-power-of-plte-and-aws-cloud-to-optimize-ami-2-0-outcomes/.
- Bernstein, Andrey. Final Report for ARPA-E NODES “Real-Time Optimization and Control of Next-Generation Distribution Infrastructure” Project. Golden : National Laboratory of the Rockies, 2021.
- Castellaw, Caleb. CMMS Pricing Guide 2025. CMMS Software. [Online] LLUMIN, 2025. [Cited: February 3, 2026.] https://llumin.com/blog/cmms-pricing-guide-2025/.
- Snyder, Aaron. How AMI 2.0 is powering the grid of the future. UtilityDive. [Online] UtilityDive, November 3, 2025. [Cited: February 3, 2026.] https://www.utilitydive.com/spons/how-ami-20-is-powering-the-grid-of-the-future/803806/.
- Office of Electricity. Voices of Experience: New Guide Offers Utilities’ Insights on Engaging with Smart Grid Customers. Electricity Industry Insights. [Online] U.S. DOE Office of Electricity, July 11, 2013. [Cited: February 3, 2026.] https://www.energy.gov/oe/articles/voices-experience-new-guide-offers-utilities-insights-engaging-smart-grid-customers.
- United States Department of Energy. Grid Resilience and Innovation Partnerships (GRIP) Program. Federal Fijnancing Tools. [Online] Grid Deployment Office. [Cited: February 3, 2026.] https://www.energy.gov/gdo/grid-resilience-and-innovation-partnerships-grip-program.
- Berg Insight. 94 percent of all electricity meters in North America will be smart in 2029. Press Releases. [Online] Berg Insight, June 7, 2024. [Cited: February 3, 2026.] https://www.berginsight.com/94-percent-of-all-electricity-meters-in-north-america-will-be-smart-in-2029.
- Office of Electricity Delivery & Energy Reliability. Smart Grid Investment Grant Program Final Report. Washington, D.C. : US Department of Energy, 2016.
- Office of Electricity. DataGuard Energy Data Privacy Program. Office of Electricity. [Online] U.S. Department of Energy. [Cited: February 3, 2026.] https://www.energy.gov/oe/dataguard-energy-data-privacy-program.
- Cappers, Peter, et al. Quantifying the Impacts of Timebased Rates, Enabling Technology, and Other Treatments in Consumer Behavior Studies: Protocols and Guidelines. Environmental Energy Technology Division. [Online] July 2013. [Cited: February 3, 2026.] https://eta-publications.lbl.gov/sites/default/files/lbnl-6301e.pdf.
If you have any updates or would like to suggest a new technology, please let us know by filling out this form.