Dive Brief:
- Wider deployment of high-resolution sensing capabilities at the grid’s edge and policy support for non-wires alternatives could significantly reduce the need for costly distribution system upgrades over the next decade, panelists said on an Aug. 22 webinar presented by Heatmap Labs and Sense, a grid edge software provider.
- Grid edge sensors and software being rolled out in Massachusetts, New York and other markets can gather millisecond-level data from individual customers, potentially enabling far more effective distribution grid operation, panelist and Sense CEO Mike Phillips said.
- Policies that promote wider advanced metering infrastructure, or AMI, deployment and curtail utilities’ financial incentives for physical capacity investments could help contain customer rates and mitigate backlash to the energy transition, Phillips said.
Dive Insight:
Talk of advanced metering infrastructure as if its deployment remains far in the future is belied by facts on the ground, Phillips said.
National Grid is installing 5,000 Sense-enabled smart meters each week in New York. It aims to outfit its entire customer base in the state with about 1.7 million meters by 2027 and begin installing an additional 1.3 million Sense-enabled smart meters in Massachusetts and Rhode Island early next year.
Sense-enabled meters pair with a smartphone app that can take 1 million voltage measurements per second, enabling vastly more visibility into grid-edge dynamics than conventional smart meters operating at 15-minute intervals, panelists said. For example, high-resolution meter data can show the precise location and timing of power flow disruptions caused by vegetation, which typically occur on timescales measured in milliseconds, Phillips said.
Xcel Energy expects to complete smart meter installations across its seven-state territory next year, said panelist Dave Mino, a Colorado-based distribution system planning and strategy manager for the investor-owned utility.
Despite operating on a 15-minute measurement interval, Xcel’s smart meter fleet will produce a library of historical data that will help the utility develop and market customer programs, improve functionality for customers with behind-the-meter solar, enhance system operators’ monitoring and control capabilities, and inform longer-range distribution system forecasting, Mino said.
In partnership with Kevala, a grid intelligence provider, Xcel is studying how to integrate AMI data into “bottom-up” forecasts for a range of future load scenarios over the next 30 years, Mino said.
AMI data is a critical complement to grid data from other sources that measure power flows at specific points or regions of the grid, such as remote terminal units and supervisory control and data acquisition systems, said panelist Mads Almassalkhi, an associate professor in the Department of Electrical and Biomedical Engineering at the University of Vermont.
“[The goal is to use] data to make better decisions [and] inform better models,” Almassalkhi said. “More data … makes our models better.”
As uptake of bidirectional distributed energy resources increases, SCADA and remote terminal unit data is necessary but no longer sufficient, underscoring the need for more high-resolution AMI data, Phillips said.
“We have a lot of assets dispersed throughout the system giving good information,” he said “Once we finally deploy AMI, we will be able to leverage a lot more.”
Distribution grid models should be flexible and capable enough to answer immediate questions like “should I charge this EV now” and while solving longer-range puzzles like which infrastructure upgrades to make over the next 10 years, Almassalkhi said.
Phillips likened the progression from AMI 1.0 to AMI 2.0 and beyond to the development of mapping apps that leverage high-frequency smartphone location data. An iPhone network that sends location data at 15-minute intervals to Verizon, then on to Google at 3-hour intervals, “would not be an engaging consumer application and would not give us what we have now, which is real-time traffic [visibility] supported by edge devices reporting where they are,” he said.
Real-time distribution grid visibility is a precursor to more effective distribution grid operation using distributed “levers” like actuators, motors and power electronics, Almassalkhi said. In Vermont, Green Mountain Power aims to improve grid resilience through dynamic management of distributed battery systems, while Vermont Electric Cooperative is using inverters to inform distribution set points, he added.
For utilities like Xcel, which is “at an inflection point [in Colorado] for load growth from electrification of premises and vehicles,” high-resolution distribution grid visibility will enable more effective capacity investments, including non-wires alternatives, Mino said. Xcel’s recent Colorado distribution system plan included two requests for proposals for non-wires alternatives, he noted.
Better distribution grid data could help convince utility regulators of the value of capital-light grid investments over costly infrastructure upgrades as the pace of electrification accelerates, Phillips said.
“There is danger of a backlash to the energy transition if it drives up costs for consumers,” he said.
