Of all the megatrends affecting the utility industry today, the electrification of transportation through electric vehicle (EV) adoption is one creating some of the biggest challenges for utilities as they plan for their future. Util-Assist is excited to make Grid4C’s AI-powered insights on EV adoption available to our clients in 2021 as part of our overall strategy to help utilities harness the full power of their AMI investment.

According to Bloomberg New Energy Finance, global ownership of EVs, now approaching 10 million, is expected to climb to 116 million by 2030. Although adoption varies widely across regions, it is expected that by the end of this decade, EVs will account for 30% of the global vehicle fleet. The implications of this for utilities are becoming increasingly  significant in terms of how we design and operate our power grids, how we procure supply, and even how we engage customers.

Surprisingly, utilities by and large still have little visibility into how EVs are affecting their business. Although ownership details are becoming more accessible to utilities, there are large numbers of EVs operating within the electric grid that utilities are, for the most part, unaware of. Projections around adoption rates are changing rapidly, making long-term forecasting difficult at best. Add to that the wide variability in charging patterns of individual customers, and the different types of charging systems used, and the picture becomes even more blurry. 

Leading utilities and retail energy providers worldwide are now turning to their AMI investments to provide more insights and transparency into how EVs are affecting their business today, and what that will mean for their future. By applying AI-enabled analytics and machine learning to interval data from installed smart meters, utilities are now able to quickly identify EV load within the customer’s consumption profile and make better decisions around key parts of their business including:


  • Placement and positioning of storage technology
  • Real-time orchestration of distributed energy resources
  • Design and targeting of new rate structures and programs
  • Tailoring alerts and communications around optimal charging time
  • Detection of anomalies and faults within the charging infrastructure
  • Implications for design, planning and operation of distribution networks
  • Improving the accuracy of demand forecasts at all levels across the power grid


Electric Vehicle Predictive Analytics

Grid4C’s AI-powered insights, provided by Util-Assist, are helping utilities across North America address these challenges head on. Since 2013, Grid4C has been at the leading edge of AMI-enabled load disaggregation, usage predictions, and appliance-level anomaly and fault detection. Grid4C’s solutions help utilities and customers anticipate the impacts of changing customer behaviours and extract more value from behind-the-meter technologies, such as solar, EVs, and smart home technologies.

“Despite the fact that AMI data has existed for years, it’s still a hugely underutilized asset with a tremendous amount of potential,” said Bob Champagne, General Manager of North America for Grid4C. “Through our AI-powered-grid-side and consumer-side analytics solutions, utilities are able to quickly assess and predict how EVs will impact key pockets of their network infrastructure and more confidently plan for their future.”