EV Infrastructure
Advanced

Optimize electric vehicle networks by strategically deploying charging solutions and managing grid impacts

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The comprehensive EV infrastructure platform

Our advanced analytics provide EVSE developers, OEMs, and other stakeholders with the insights needed to build a reliable charging network and manage the increased grid load effectively, ensuring a seamless transition to a more electrified future.

Optimize Electric Vehicle Charger Placement

Increase the speed and analytical accuracy of early stage project development and minimize operating costs by evaluating parcel and land use data, geospatial road network data, grid infrastructure data, and vehicle adoption data in one platform.

Forecast and Plan for EV Adoption

Granularly model where EVs will be adopted to the level of detail that is required to meet the range of scenarios regulators and policymakers are envisioning.

Maximize EVs as Key Distributed Resources

Simulate high EV penetration effects and explore various scenarios, including different rate structures and charging locations, to assess how vehicle charging impacts grid load dynamically.

Drive Change Management and Strategic Transformation

Leverage Kevala's Professional and Advisory Services, a skilled team of industry professionals and researchers, to enhance platform insights, speed up adoption, and achieve strategic success.

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Unprecedented insights into EV-to-grid integration

Electric Vehicle Supply Equipment Interconnection Planning

Accelerate and simplify the time and complexity of today's onerous interconnection process.

Grid Carbon Intensity

Understand the full picture of locational grid carbon intensity to support EV-related operational and siting decision making that informs decarbonization initiatives.

Non-Wires Alternatives

Quickly evaluate and validate non-wires alternatives in a fully integrated platform with superior visualization capabilities.

Distributed Energy Resource Adoption Modeling

Precisely and confidently estimate the likelihood of DER adoption at the customer level with detailed spatial and locational granularity.

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