Electric vehicles provide financial upside to electric utilities and ratepayers
New Berkeley Lab study quantifies the rate and utility earnings impacts of electric vehicles under a range of deployment scenarios
Widespread electric vehicle (EV) adoption is critical for meeting economy-wide decarbonization goals. As a result, states are considering enabling policies and retail electricity rate designs that accelerate EV deployment. EVs may provide possible financial upside to electric utilities and their ratepayers in several ways. For example, from the utility perspective, EVs could drive increased electricity sales and new earnings opportunities through increased capital investments. From the ratepayer perspective, increased electric loads from EVs could reduce average all-in retail rates. Whether there are net benefits or costs to utilities and/or ratepayers depends critically on how EVs are integrated and managed through enabling grid investments and charging strategies.
We are pleased to release a new study from Lawrence Berkeley National Laboratory, and with collaboration from Lumina Decision Systems, titled “Quantifying the Financial Impacts of Electric Vehicles on Utility Ratepayers and Shareholders.” The study estimates the utility earnings and customer rate impacts of EVs using a bookend approach of low peak impact (i.e., best case) and high peak impact (i.e., worst case) charging strategies for a generic summer-peaking, investor-owned, and vertically integrated utility. The study uses Berkeley Lab’s Financial Impacts of Distributed Energy Resources (FINDER) model that mimics the electric utility investment planning and ratemaking processes over a 20-year analysis period.
The study findings, published in slide-deck format and a supplemental information document detailing key assumptions and methodology, are available here. The authors will host a webinar presenting the results of the study on February 22 at 2 PM Eastern / 11 AM Pacific. Register here: https://lbnl.zoom.us/webinar/register/WN_dKxjy7I2RK2ha_Wyiehiog
The study finds that shifting EV charging away from utility system peak demand periods reduces average retail rates ~0.8%-1.0% by lowering incremental generation and distribution system investment costs. This suggests that pricing and programs to encourage non-coincident peak charging are highly beneficial from the ratepayer perspective. Shareholder earnings are also reduced under a low peak impact charging strategy (~1.9%-2.4%), because reductions in new generation and distribution infrastructure investments erode some of the incremental earnings. It’s important to note, however, that utility shareholders are still better off compared to a future without EVs.
Large initial utility infrastructure investments enable both greater EV deployments and greater long-term decreases in retail electricity rates. In a case of high EV penetration levels, large early infrastructure investments cause retail electricity rates to initially rise ~1.6%, but increases in sales from EV load cause retail electricity rates to decline ~2.9% in the later years of the analysis period. A forward-looking, long-term perspective can overcome near-term rate increases and enable long-term decreases. Overall, the rate impacts in this study are quite small on a total utility basis; but, they could be more significant for particular customer classes depending on approaches to cost allocation and cost recovery, which are not explored in the study.
We also examined the sensitivity of results to different assumptions of EV deployment characteristics, EV impacts on retail electricity sales, incremental distribution system costs, EV charging location, and utility EV enablement costs (i.e., utility costs to invest in EV charging, controls, and communication to deliver and administer EV programs). Although results were directionally consistent across sensitivity cases, we found that EV deployment characteristics matter and present important tradeoffs between utility cost reductions and efforts to encourage EV adoption.
We thank the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy Strategic Analysis Team for their support of this work.