New capability analyzes the travel patterns of residents of disadvantaged communities to identify charger locations that will maximize convenience and utilization

Volta Inc. (NYSE:VLTA) ("Volta"), an industry-leading electric vehicle (EV) charging and media company, today announced that its infrastructure planning solution, PredictEV®, now offers state and local governments data-driven insight into the travel patterns of disadvantaged community (DAC) residents to identify EV charger locations that will maximize convenience and utilization with more precision. The new feature further ensures infrastructure funds are efficiently and effectively spent as governments develop competitive applications for the Charging and Fueling Infrastructure Discretionary Grant Program that uphold the federal government's Justice40 goal.

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Volta Expands PredictEV® Capabilities That Support the Federal Government's Justice40 Initiative and Enhance Community Charging Grant Applications (Photo: Business Wire)

PredictEV is an advanced infrastructure planning solution that analyzes disparate data sources, including local mobility, demographic, commercial, and site-specific data, to precisely answer questions about expected EV adoption, optimal charger locations, and the right mix of charging infrastructure. Today's update builds on PredictEV's recent incorporation of census tract data that identifies DACs by adding the ability to also analyze the most popular vehicular travel routes of residents from these areas.

"Combining these two datasets supports effective public EV charging infrastructure planning for disadvantaged communities, which is critical for accelerating EV adoption within these regions due to the limited availability of at-home charging," said Brandt Hastings, Chief Commercial Officer at Volta. "Often, the best locations to place chargers will be in highly-trafficked areas within DACs. Other times, PredictEV's travel data may reveal that constructing an EV charger at a shopping center in an adjacent community will result in significantly higher utilization due to the popularity and convenience of that location."

PredictEV has been used by Alabama's Department of Economic and Community Affairs (ADECA) to develop its Electric Vehicle Infrastructure Plan, and its insights informed Volta's collaboration with the City of Irving and the State of Michigan and DTE Energy. Electric utilities, including Southern Company, Southern California Edison, and Tucson Electric Power, also use the planning tool to forecast EV charging demands on the grid.

Hastings continued, "Volta is committed to supporting Charging For All. We look forward to continuing our work with governments as they design future-forward eMobility infrastructure plans that maximize taxpayers' dollars and provide vital infrastructure to disadvantaged communities."

Government agencies and community organizations developing EV charging infrastructure strategies and grant applications can learn more about PredictEV by visiting https://voltacharging.com/predictev or by emailing predictev@voltacharging.com.

About Volta

Volta Inc. (NYSE:VLTA) is an industry-leading electric vehicle ("EV") charging and media company. Volta's unique network of charging stations powers vehicles and drives business growth while accelerating a clean energy future. Volta delivers value to site partners, brands, and consumers by installing charging stations that feature large-format digital advertising screens located steps away from the entrances of popular commercial locations. Retailers can attract and influence foot traffic, advertisers can precisely target audiences, and EV drivers can charge their vehicles seamlessly as they go about their daily routines. Volta's extensive network leverages its proprietary PredictEV® platform, which uses sophisticated behavioral science and machine learning technology to help commercial property owners, cities, and electric utilities plan EV infrastructure intelligently, efficiently, and equitably. To learn more, visit www.voltacharging.com.

Forward-Looking Statements

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