The rising tide of EV adoption poses a critical challenge for grid operators and distribution utilities: Unmanaged EV charging creates erratic and hard-to-predict peak load spikes that can overload critical equipment, drive up operational costs, and threaten reliability. Traditionally, distribution utilities build more substations, transformers, and other infrastructure upgrades to accommodate increased peak demand in a given part of the grid.
However, most utilities do not have visibility to all of the EVs charging on their grid, which makes efficiently planning for location-specific upgrades impossible – and to implement blanket grid infrastructure upgrades without a plan would be impractical, time-consuming, and extraordinarily costly.
By enhancing grid-edge awareness, assessing the local impacts of EV adoption, and developing driver engagement programs, utilities can not only more confidently plan for the impacts of EV adoption, they can also unlock the ability to leverage EVs as flexible, controllable assets to bolster affordability and reliability.
Improving grid-edge awareness is the first and most important step to planning effectively for an EV-integrated grid. In order to plan appropriately for grid operations and predict future load growth, utilities need to know where EVs are being added on the grid and when they are charging – regardless of enrollment in utility programs. In fact, by industry estimates, for every EV charger enrolled in a utility program, there are 2 unenrolled chargers.
To detect EVs that are “invisible,” utilities can analyze meter-level load data from advanced metering infrastructure (AMI) to identify meters that exhibit charging behavior but aren’t actively participating in a utility program. This data can be aggregated to map out areas with high EV adoption and ones likely to see future growth, which is critical data for informing accurate planning and forecasting.
As smart meters now make up roughly 70% of all U.S. electric meters, utilities have a wealth of meter data at their fingertips. Utilities looking to better plan for EV impacts should leverage their existing data to disaggregate EV charging loads as a first step. While many utilities will still choose to invest in direct EVSE or telematics-based integrations, disaggregation of AMI data is a low-cost and effective way to gain visibility into where EVs are charging.
Once an EV detection approach has been established, upline transformer loading analysis can put EV charging in context to help utilities strategically prioritize short- and long-term upgrades. If unmanaged, EV charging can quickly overload upline equipment, especially transformers – which means more budget and more time must be allocated toward replacement equipment, truck rolls, and utility overhead.
The current wait time for a new service transformer has jumped up to three years, so utilities have extra incentive to reduce the frequency of transformer upgrades. With transformer loading analysis, utilities can not only analyze usage trends across the entire fleet, but also pinpoint individual overloaded transformers and map them to EVs and other DERs that might be impacting utilization. This lays the foundation for thoughtful capital planning – identifying where upgrades will be required and where proactive mitigating, such as managed charging programs or time of use rates, can help defer or avoid upgrades entirely.
An EV managed charging program is a critical component of a utility’s long-term EV management strategy. These programs not only improve visibility and engage customers, but they also provide opportunities to cost-effectively leverage EVs as flexible resources to support reliable grid services. It’s not a small impact either. Industry experts estimate that, when aggregated into virtual power plants (VPPs), EVs and other distributed energy resources (DERs) could collectively reduce grid resource adequacy costs by $15-35 billion over the next ten years.
In addition to reducing grid management costs, utility programs create an opportunity for utilities to facilitate affordable EV adoption in low- to middle-income (LMI), frontline, and disadvantaged communities.
Rebate programs typically compensate a new EV owner for a lump sum or percentage of the cost of the EV or its charger. These programs are relatively simple to design and implement, while also providing value by maximizing the utility’s visibility of EVs on its grid. Charging incentive programs compensate the EV owner to charge during off-peak hours of the day. This reduces local congestion and equipment impacts, lowers operational costs during periods of high demand, and makes EV charging patterns and behavior easier for the utility to predict. Examples of utility managed charging programs include:
In Q1 of this year, electric vehicle (EV) sales exceeded 7% of total new vehicle sales in the U.S., up 66% from a year earlier. With dozens of passenger EV models available, federal and local incentives, and growing market momentum, EV adoption will continue to accelerate. Experts estimate that EV sales could reach 40% of new vehicles sold by 2030.
The widespread adoption of electric vehicles will have an enormous impact on the way the grid is operated, but utilities should not feel forced to choose between critical upgrades and ensuring affordability for their community members. Instead, utilities can leverage proven tools to achieve grid-wide situational awareness and orchestration of EV charging that supports an affordable, reliable, and sustainable energy future for all.
Want to learn more about EV readiness for the grid? Watch the recording from our webinar “How Utilities Can Ensure The Grid Is Ready For Electric Vehicles” where industry leaders discuss a collaborative approach to ensure the grid is prepared for EVs without breaking the bank.