Capturing the Value of EV Managed Charging Programs

Key Takeaways from Expert Panel on Measuring Electric Vehicle Flexibility

Michael Colby is a principal in Cadmus’ energy services division focused on transportation electrification. With over 16 years of experience designing, developing, implementing, and evaluating utility demand-side management, demand response, distributed energy resource, and transportation electrification programs, Michael is a recognized expert on supporting and integrating electric vehicles into the grid.

In April 2024, Cadmus’ Michael Colby participated in the EnergyHub HubSummit 2024 utility conference in Detroit, Michigan, joining the panel EV Track—Measuring EV Flexibility. Alongside Amy Martin (Vice President, Frontier Energy), Hilary Polis (Director, Opinion Dynamics), Chelsea Liddell (Sr. Data Scientist, DNV), and moderator Sarah Howerter (Data Analytics Engineering Manager, EnergyHub), the panel examined strategies for accurately evaluating the load impacts and value streams from utility electric vehicle (EV) managed charging programs.

As utilities continue to roll out more EV managed charging programs, measuring their effectiveness is critical—yet it has raised new evaluation challenges.

While methods for evaluating traditional utility demand response programs are well-established in the industry, EV managed charging programs require an updated measurement framework to accurately capture the full value of this flexible grid resource. Along with his co-panelists, Michael emphasized three key takeaways when evaluating EV managed charging programs.

Incorporate Evaluation from Day One

Too often, evaluation is an afterthought rather than being built into program design from the start. “If you don’t identify the necessary data requirements during the design phase, evaluators will be extremely limited in what they can measure and report on,” Michael cautioned.

A prime example of this is plug-in time, referring to when the EV is plugged in rather than when charging starts. This aspect can be used to model counterfactual charging behavior but is not consistently included in the data collection plan. While developing a counterfactual based on plugged-in time is not the only means of establishing a baseline, it is a valuable tool in the evaluation toolbox and is only available if the data is collected in the first place.

The solution? Engage evaluation experts early to specify data needs, determine baselines and control groups, and define success metrics upfront.

Establish a Control Group

Utilizing a control group is the preferred method for evaluating EV managed charging programs to confidently attribute results, avoid double-counting impacts from other sources such as time-of-use rates (TOU), and to avoid biases. “Without a properly constructed control group, you’re essentially evaluating in a vacuum,” stated Michael. The gold standard is a randomized control trial enabling an apples-to-apples comparison between the treatment group (i.e., participants whose charging is being managed) and an unmanaged “control” group.

However, there are limitations to utilizing a control group, including equity considerations for those in the control group (e.g., control group participants not benefiting from potential bill savings on a TOU rate), and limitations on program impacts, as control group participants will not provide program benefits such as peak demand reductions. Depending on program goals and objectives, these limitations can be addressed in the planning stage or alternative methodologies explored (such as developing a counterfactual utilizing plugged-in times).

Quantify the Full Value Stack

While peak demand reduction is often the primary goal, the flexibility EV managed charging provides can generate numerous other grid and customer benefits that warrant evaluation, including:

• Bill savings for EV owners by shifting charging to low-cost periods.
• Increased renewable energy integration by aligning charging with solar/wind generation.
• Avoidance of infrastructure upgrade costs in constrained distribution areas.
• Support for transportation electrification and emissions reduction goals.

“By comprehensively measuring and quantifying this ‘value stack’, we can demonstrate the full positive impacts of managed EV charging for utilities, ratepayers, and society,” said Michael.

Furthermore, EV managed charging programs will often fail a cost-benefit test when only quantifying the benefits at the bulk system level and disregarding benefits at the local distribution level. Incorporating these distribution level benefits (e.g., deferral of a distribution transformer upgrade) not only provides a more complete picture of the benefits that EV managed charging can offer but will enhance the cost-effectiveness of the program.

As EV adoption continues to rise and utilities aim to manage EV charging as a grid resource, accurately measuring charging flexibility through advanced evaluation approaches will be important for utilities to maximize the benefits and minimize costs. A thoughtful program design that integrates sound evaluation principles and methodologies will drive more impactful EV managed charging investments, benefiting everyone involved.

Contact Michael Colby to learn more about Cadmus’ work in transportation electrification.