Analysis of real-time data from 54,000 charging stations in the US has revealed significant differences in charging habits across California, Texas, and the Northeast.
Researchers at the University of Maryland used supercomputers and machine learning tools to analyze a year’s worth of real-time data collected from thousands of electric vehicle (EV) charging stations in three power grid zones.
It is the first study to use real-time charging port data to understand charging behaviors across different time intervals, according to researchers. It covers the majority of roughly 61,000 EV charging stations in the US that were publicly available as of February, 2024.
Researchers hope power grid operators can use their findings to set fair electricity prices, expand and improve the network of charging stations, and manage supply and demand by ensuring more charging ports are available and reducing wait times.
“Understanding EV users’ charging behaviors will provide valuable insights into their needs, enabling us to efficiently deploy EV charging infrastructure to meet the emerging demand,” said civil engineering Ph.D. candidate Safoura Safari.
The study, led by scientists at University of Maryland’s Center for Global Sustainability and Center for Disaster Resilience, utilized individual charging port statuses recorded every 10 minutes at the monitored stations.
Researchers looked for variations of charging patterns on daily, monthly, and seasonal scales.
Machine learning was then used to extract “clusters” – or groups – of behavior from the data, which also accounted for temperature impacts on battery range, as it influences charging decisions.
California ‘vulnerable’
The first round of analysis was based on data for the month of August and revealed working-hour patterns in all three zones, with differences in charging behavior and power demand.
In the California zone, about 45% of stations showed a strong working-hours charging pattern, with peak utilization reaching 80% of total stations’ charging capacity in the time period between 6 am and 6 pm.
“This suggests that charging stations in this zone may be especially vulnerable in the event of a disaster or disruption of power – with the potential for lines of vehicles to form at public charging stations,” researchers said.
Meanwhile, in Texas, about 30% of stations showed a similar workday pattern, with peak utilization averaging 60% of total capacity between 9 am and 4 pm.
In the Northeast zone comparison of six states, 28% of stations demonstrated a working-hour pattern, with peak utilization of 55% during the period of 8 am and 6 pm.
According to Safari, the variation in charging behavior between zones could be attributed to several factors, such as the price of electricity, the availability of public charging stations, and incentive programs encouraging owners to charge during off-peak hours.
Gaps in infrastructure access
Researchers will further analyze data to uncover other patterns, such as charging station usage during overnight hours, holidays, local and national events, and weather-related disasters.
Another focus of the study is to explore potential inequities in access and use of EV charging stations on a national scale.
“Our findings can set the foundation for future research on the equitable accessibility, availability, and utilization of EV charging facilities across diverse communities with varied socio-economic status,” said Jiehong Lou, assistant professor at the University of Maryland and assistant research director of the Center for Global Sustainability.
In a previously published study, Lou and his colleagues found that public EV infrastructure was less accessible to lower-income households in both urban and rural areas.
Meanwhile, a report from Pew Research Center found that only 17% of EV charging stations are located in rural areas, with the rest mostly accessible to urban residents. It said that many more charging stations are needed across the country to accommodate future EV ownership.
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