(UMTRI) On Electric Vehicle Charging Behavior Study
UMTRI has deployed Utilidata’s AI-powered technology on campus to analyze the impact of EV charging on the power grid
Ann Arbor, Michigan, May 2023 (GLOBE NEWSWIRE) — Utilidata, an industry-leading grid-edge technology company, recently announced a research partnership with the University of Michigan Transportation Research Institute (UMTRI) to study the relationship between electric vehicle (EV) driving and charging behaviors to better understand how those behaviors impact the electric grid. Below we share a question and answer set with guest Josh Brumberger, Chief Executive Officer of Utilidata, who has a proven track record of success spanning the public and private sectors.
Q.) Could you tell me more about your background?
Throughout my career, I have been deeply involved in navigating the intersection of business and public policy – serving in senior roles at the Office of the Rhode Island General Treasurer as well as national political campaigns. Working in both the public and private sectors, I’ve accumulated a diverse range of experiences that have informed my view that great technology alone is not enough; it’s also about the ability to bring people together and the will to make a change. With that focus, Utilidata strives to make meaningful change by engaging all stakeholders – technology, public policy, utilities, and community advocates.
Q.) What is Utilidata’s history?
Utilidata was founded in 2012. We developed software technology to improve the efficiency and operations of the distribution grid through real-time grid control and decision-making.
As more people adopt electric vehicles, distributed solar, batteries, and heat pumps, we realized there is a need for decentralized decision-making and to bring that real-time visibility to the edge of the grid, where electricity connects to customers at their homes and businesses. So, we shifted our focus a few years ago to the edge of the grid where there is the most complexity and where the most change occurs – as it’s the critical nexus between customers, their investments in clean energy, and the utility system.
Q.) What is Utilidata’s mission and how is this accomplished through its products?
After over a decade of developing software technology to improve the efficiency and operations of the distribution grid through real-time grid control and decision-making, we shifted our focus to the edge of the grid – where electricity connects to customers at their homes and businesses.
Utilidata is bringing distributed AI to the edge of the grid to accelerate the clean energy transition and better serve utility customers. Not only is this where the most change occurs on the grid, but it’s also the most complex due to a lack of real-time data collection and analysis. As more people begin to adopt clean energy systems, such as EVs, solar panels, and heat pumps, there is a need for more data and decentralized decision-making to make it easier for utilities to integrate and manage these systems without causing grid instability. That’s where we come in.
Our smart grid chip, powered by NVIDIA, the world leader in accelerated computing and AI, was developed to improve the efficiency and operations of the distribution grid through real-time grid control and decision-making. The smart grid chip is currently installed on a meter, using a meter adapter, to collect live data from every customer endpoint.
The smart grid chip uses on-chip and cloud-based software to provide utilities with granular data and real-time visibility of grid conditions to:
● Increase grid capacity and accelerate solar connection waiting periods
● Manage EV charging demand
● Reduce/offset expensive infrastructure upgrades
● Avoid outages and recover from outages quickly
Q.) What were the main objectives and motivations behind forming the partnership between Utilidata and UMTRI?
Our main motivation stemmed from a shared understanding that more research on the grid’s edge is critical to prepare it for energy demand influxes. EVs are projected to make up almost 50 percent of all car sales by 2030, meaning Michigan’s infrastructure will need to be strong enough to support 2 million EVs by that time. Currently, the data doesn’t exist to estimate how to best prepare our grid for this. Through this partnership, we’re aiming to collect robust data to not only better understand EV charging patterns, but to manage their demand on the grid and support the widespread adoption of electric vehicles in a sustainable way.
Q.) What data is being collected with the smart grid chips?
UMTRI has installed our smart grid chips on several EV charging stations across the University of Michigan’s campus to collect real-time voltage, current, and power data. This gives UMTRI researchers the opportunity to detect EV charging patterns and how it impacts the grid by gathering data from the edge. The smart grid chips also allow us to learn more about grid conditions and demand in real-time, such as where a power outage occurred or if a location is underrated for power.
The study participants have a vehicle monitoring device installed on their EV that collects data on their start and stop time for charging, location of charging, trips taken, and acceleration/deceleration. From this, UMTRI can compare smart grid chip data to vehicle data, helping us better understand what is happening on the grid and the vehicle.
Q.) What brings you to Michigan to help conduct this research?
Michigan has been a part of our smart grid chip journey from the very beginning. Utilidata’s Business Development Lead is a University of Michigan alum who connected us with Ann Arbor-based Endectra, a University of Michigan spinout, to prototype the first several generations of the smart grid chip product. Recently, we’ve partnered with Brooks Utility Products to begin manufacturing Utilidata’s smart grid chips right here in the United States. Brooks’ location in Michigan has opened up many
opportunities for us to bring Utilidata into the region’s growing tech market, as seen with this partnership and the development of our innovation lab in Ann Arbor.
Q.) What excites you the most about this partnership?
It excites all of us working on this project to think about the potential impact this collaboration could have on preparing our grid for the adoption of electric vehicles and helping pave the way toward a more sustainable future. For us to see real change, we need to dive deeper into determining how we can prepare our current infrastructure to see a better tomorrow. Having the opportunity to combine our smart chip technology with UMTRI’s renowned expertise in transportation research is a great first step. We’re excited to keep pushing forward long after the results are in.
Q.) Why does the grid need accelerated computing and distributed AI?
The clean energy transition brings new and complex challenges to how the electric grid is operated. The way we supply and consume energy is becoming increasingly complex with the rapid increase in solar, electric vehicles, storage batteries, and electric home heating. The grid is antiquated and unprepared to manage these new complexities and requires advanced technology to provide safe, clean, reliable, and affordable energy.
Most modern industries, including transportation, shipping, internet service, and healthcare, are using distributed computing with AI-enabled tools to improve operations and manage complex and decentralized systems. On the grid, these technologies will enable grid operators to predict grid conditions and recommend decisions in real-time.
Processing data locally with accelerated computing allows grid operators to respond at the pace of change. The millions of distributed energy resources need to be strategically orchestrated to shift consumption and generation based on current grid conditions, reducing the demand to better match the supply of clean energy resources. Today, grid operators are manually forecasting and monitoring energy loads with minimal automation. Distributed computing with AI-enabled tools identifies patterns in large volumes of data and makes predictions to enable operators to better utilize grid assets in real-time and make split-second decisions based on different scenarios.
Shared below as reference is the rest of the original press release:
Utilizing Utilidata’s smart grid chips, a first-of-its-kind distributed artificial intelligence (AI) platform, researchers have installed the technology on several EV charging stations across the University of Michigan’s (U-M) campus to collect data on the impact on the grid.
Utilidata’s smart grid chips are collecting real-time voltage, current, and power data at the edge of the grid, allowing researchers to analyze and detect EV charging patterns at each location. This data will be analyzed alongside vehicle data from a group of participants within the research study who have a vehicle monitoring device installed on their EV. Data from the monitoring device includes start and stop time for charging, location of charging, trips taken, and acceleration/deceleration. Closely analyzing driving and charging behavior will lead to a better understanding of how to manage EV demand on the grid and help utilities develop customer-smart charging programs. As UMTRI researchers continue to collect and analyze data, they’ll have access to the recently announced U-M Electric Vehicle Center for further collaboration. Results from the UMTRI study are anticipated later this year.
“As more people invest in electric vehicles, our electric grid needs to be ready to support the influx in energy demand. We’re thrilled to have partners like UMTRI whose research and studies have made major, lasting impacts on the transportation industry,” said Josh Brumberger, Utilidata’s Chief Executive Officer. “Access to real-time insights of when EVs are charging will help utilities identify charging locations and design better EV programs for customers.”
The study with UMTRI follows the recent news on Utilidata’s new innovation lab and its commercial manufacturing partnership in the state of Michigan.
“As we transition to electric transportation, the industry needs cutting-edge technologies, like Utilidata’s smart grid chip, to meet the moment and bring us into the future”, said Jim Sayer, UMTRI director. “Partnering with Utilidata allows us to combine their energy and grid expertise with our decades of experience in conducting large-scale research projects, data collection, and deployments that lead to a safer, more efficient, and equitable transportation and mobility future.”
EVs are projected to make up almost 50 percent of all car sales by 2030, and Michigan’s goal is to build the infrastructure necessary to support 2 million EVs on its roads by that time. As the transition to cleaner technologies continues, specifically in the automotive space, understanding the potential impact of these new technologies on the grid will be crucial. Utilidata’s smart grid chip, powered by the NVIDIA Jetson platform, is a new distributed AI platform installed alongside electric meters to integrate more distributed energy resources (DERs) including solar, battery storage, and EVs, and enhance the resiliency of the electric grid. Leveraging NVIDIA’s accelerated computing and AI technology, the smart grid chip collects and analyzes large amounts of data at the edge of the grid to provide utilities with real-time visibility of grid conditions.
About Utilidata:
Utilidata is a technology company bringing distributed artificial intelligence (AI) to the edge of the electric grid to accelerate decarbonization and better serve utility customers. The company’s smart grid chip, powered by NVIDIA, is the utility industry’s first scalable distributed AI solution and provides an open, scalable, and future-proof platform for grid operations. For more information, visit utilidata.com or follow @Utilidata on Twitter
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