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The State of Michigan has launched a pilot program to optimize electric vehicle (EV) charging using artificial intelligence (AI) technology. Funded by a $170,000 grant from the Office of Future Mobility and Electrification (OFME), the initiative brings together Rhythmos.io and Consumers Energy to implement an AI-powered solution in Grand Rapids. The project seeks to double the EV charging capacity from existing utility infrastructure while reducing costs for both energy providers and customers. By addressing the growing demand for EV charging, this effort could set a precedent for sustainable grid management across the United States.
Key Highlights
- $170,000 grant funding from the State of Michigan
- Collaboration between Rhythmos.io, Consumers Energy, and Optiwatt
- Focus on optimizing EV charging to minimize grid strain and lower expenses
- Potential to double EV charging capacity without costly infrastructure upgrades
- Supports Michigan’s leadership in clean energy and mobility innovation
The pilot targets Level 2 EV charging locations in Grand Rapids, monitoring their effects on the distribution system. It will engage existing EV drivers in an optimized charging program that shifts usage to off-peak hours, reducing infrastructure costs and customer bills. Success will be evaluated through metrics like the accuracy of identifying charging sites, the extent of load shifting, and the resulting cost savings.
At the core of the project is Rhythmos.io’s CadencyEdgeAI℠ platform, which leverages advanced analytics to manage EV charging at the grid edge. Paired with Optiwatt’s platform, a leader in smart charging with a vast EV driver community, the system optimizes charging schedules to ease grid pressure and cut costs for utilities and users alike.
Justine Johnson, chief mobility officer for the State of Michigan, stated, “This initiative showcases how mobility technology can address real-world challenges. By enhancing grid reliability and making EV adoption more cost-effective, we’re positioning Michigan at the forefront of clean energy innovation.”
The pilot’s success could have far-reaching implications for U.S. energy providers. As EV adoption grows, utilities face rising infrastructure demands. This optimized charging approach could save billions in upgrade costs while maintaining reliable service. A study by Energy and Environmental Economics (E3) reinforces this, noting that optimized EV charging could reduce transformer upgrade costs by up to 60% compared to unmanaged charging.
The Michigan pilot’s outcomes will be closely observed by industry leaders and policymakers, potentially offering a blueprint for sustainable EV integration into power grids nationwide. Results will be shared in a detailed use case study, highlighting economic and technical benefits.
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