Charged EVs | Volta’s PredictEV planning platform helps local governments site chargers in disadvantaged communities

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by Kivi

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11.16.2022


Volta, which calls itself “a charging and media company,” makes an infrastructure planning platform called PredictEV, which is designed to help state and local governments to identify optimal charger locations in disadvantaged communities.

“This analytical capability aligns with the federal government’s Justice40 goal, which seeks to ensure 40 percent of the overall benefits of certain federal investments, including the $7.5 billion allocated to EV charging infrastructure under the Bipartisan Infrastructure Law, flow to disadvantaged communities,” says the company.

Volta’s PredictEV analyzes various data sources, including local mobility, demographic, commercial and site-specific data, to help identify optimal charger locations and the right mix of charging infrastructure.

Customers include Alabama’s Department of Economic and Community Affairs, the State of Michigan, Southern Company, Southern California Edison and Tucson Electric Power.

“An inclusive mobility ecosystem must be built as a resource for all communities, including those in lower-income and environmental justice-impacted areas, and our state has made a conscious effort to ensure these communities have the same mobility opportunities that other regions do,” said Michigan’s Chief Mobility Officer Trevor Pawl. “Thanks to the availability of disadvantaged community data, we can further optimize our EV mobility solutions to support Michigan’s residents as they move around the state.”

“The health and safety of our planet demands that every community is able to participate in the transition to electric mobility,” said Vince Cubbage, Interim CEO at Volta. “PredictEV’s latest capabilities are another example of Volta’s commitment to providing our partners with data-driven electrification planning to deliver focused equity and economic-impact insights that ensure the most efficient use of federal funds.”

Source: Volta





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