Training
Website
Charging Smart
Grid Up: Accelerating Charging in Communities (GUACC)
Insights From Real-World Driving Data
This charging tool forecasts when and where energy and power demand will arise from vehicle electrification. The tool leverages real-world granular trip data to provide users greater insight into how driving behavior will shape the need for future electric vehicle charging equipment (EVSE).
Planning for the Future
Users will be able to identify areas for proactive investments in the grid where the future growth of EV charging demand is clearly established, enabling rapid EV adoption and supporting cost-effective buildout of needed infrastructure.
Access the tool above.
Using GUACC for Charging Smart Designation Criteria
The GUACC tool can provide relevant data to support the achievement of Charging Smart designation criteria.
GUACC can be utilized to create data-driven goals and plans for local EV adoption. The scale of anticipated EV demand, as informed by this data, can guide the development of community-wide EV goals, estimate the number of charging ports required for planning documents, and support the development of local comprehensive plans. This is particularly useful for state and city officials seeking to incorporate EV and supporting infrastructure goals into their planning activities.
GUACC can be used to support initiatives for utility planning and engagement. Granular EV load forecasts can be used to engage with the utility on the need for grid upgrades and charging program development. This includes understanding energy consumption and peak demand at the census block group level as EV adoption increases through 2050. Additionally, the tool emphasizes the importance of promoting effective charge management practices to reduce peak demand and, thus, the need for electric upgrades. This is particularly useful for government officials seeking to collaborate with utilities to deliver services to the city and its residents efficiently and cost-effectively.
GUACC can be used to support decision-making for government initiatives to provide public charging. For example, this data can identify the areas in a community (down to census block groups) expected to have the highest demand for public chargers through 2050, presenting viable locations for public charging programs. This can also be overlaid with housing density data to prioritize charging in areas with high multi-family housing.
GUACC can inform data-driven planning for shared mobility services. Census-block group level charging demand forecasts provide insight into local travel patterns and associated charging needs, identifying where shared car and micromobility programs can address EV access gaps (especially in low-income areas) and present opportunities for mode shift and VMT reduction.
GUACC provides supporting data to inform the development of EV-encouraging local regulations, public awareness campaigns, and financial incentives to support EV adoption. Highlighting the scale of charging needed in the near future at various types of locations can help make the case for zoning and planning reform to streamline charger installation. EV demand forecasts, particularly in communities with slow uptake and those with high shares of multi-family housing, can help identify the need and size of economic incentives that may support EV uptake.