Energy Systems Integration Group Unveils New EV Load Forecasting Guide for Utilities and Regulators

The Energy Systems Integration Group has released a new guide aimed at helping utilities and regulators better anticipate the impact of electric vehicles on the grid.

The EV Load Forecasting Guide outlines core principles, synthesizes leading industry practices, and provides direction for developing forecasting approaches tailored to electrified transportation. The publication comes as utilities face growing pressure to plan for new sources of demand while maintaining reliability and managing costs.

Forecasting plays a central role in utility planning, underpinning billions of dollars in grid investment. Traditionally, these forecasts have been based on economic and population trends. However, the rise of electric vehicles introduces added complexity. EV charging patterns are influenced by human behavior, can shift geographically, and may concentrate in ways that strain local distribution systems if not properly anticipated.

“It is more important than ever to understand where and when EV charging loads will arrive on the grid,” said Greg Mandelman, director of analytics and energy programs at Electric Power Engineers and a lead author of the guide. He noted that the issue is particularly pressing as planners and regulators contend with rising load growth, affordability concerns, and increasing grid complexity.

As EV adoption expands, so does the need for updated forecasting methods. According to the guide, the load from a single electric vehicle can approach nearly half the annual electricity consumption of an average U.S. household, and that demand can emerge more quickly and unpredictably than traditional sources.

The report emphasizes that effective EV load forecasting must account not only for total demand, but also for when and where that demand will occur. It describes forecasting as a critical planning tool that can help evaluate solutions, reduce the risk of service delays, and avoid inefficient infrastructure investments.

Scenario analysis is highlighted as an increasingly important technique, allowing planners to assess a range of potential outcomes and better manage investment risk while designing a more flexible grid.

“This ESIG guide provides stakeholders across the spectrum with detailed, actionable, and vetted approaches that equip them to develop the EV load forecasting methods that will best serve each jurisdiction with its unique needs,” said Matthew Schuerger, senior fellow at ESIG.

The guide’s recommendations were developed with input from an industry advisory group, a regulatory advisory group, and interviews with subject matter experts. It identifies 20 best practices across key components of EV load forecasting, including scoping, implementation, and review, as well as applying forecasts to grid planning, improving coordination and data sharing among stakeholders, and incorporating emerging technologies and modeling advances.