Grid Impact Model Resources for Managed EV Charging and Distribution Planning
The Grid Impact Model (GIM) resource page provides links to executive summaries, technical papers, presentations, videos, demonstrations, and planning resources covering localized EV load forecasting, managed EV charging program evaluation, distribution planning, and utility financial analysis.
- Forecast localized EV adoption, charging loads, and weather-sensitive hourly distribution system impacts.
- Evaluate managed EV charging technologies, implementation costs, customer participation, and G&T peak demand reduction strategies.
- Support feeder, transformer, neighborhood, ZIP Code, and block group distribution planning with localized hourly load forecasts.
- Compare program financial performance, avoided infrastructure costs, and utility revenue impacts under alternative managed charging scenarios.
- Export localized load forecasts for use in CYME, Synergi, WindMil, OpenDSS, GIS, and other utility planning tools.
- Provide planning resources for utility executives, distribution engineers, consultants, and electric cooperative program managers.
Grid Impact Model Summary
The Grid Impact Model (GIM) is an Excel-based planning system that helps electric cooperatives evaluate the localized impacts of growing EV adoption and determine the most effective managed EV charging strategy for their distribution system. Using identity-protected customer data and AI-assisted customer digital twins, the model forecasts hourly EV and residential loads at the ZIP code, block group, neighborhood, and customer level.
The Grid Impact Model enables utilities to compare managed EV charging alternatives, evaluate different communications and control technologies, estimate reductions in G&T coincident peak demand, and quantify the financial performance of alternative program designs through an integrated business case analysis
Utilities can also evaluate customer growth, building electrification, weather extremes, demand response strategies, distributed energy resources, and virtual power plant (VPP) scenarios using flexible assumptions, intuitive scenario analysis tools, and real-time visualizations that make complex planning decisions easier to understand and communicate.
The result is a practical planning tool that combines localized forecasting with financial analysis to support utility investment decisions.
Executive Planning Questions
The Grid Impact Model helps utilities answer four critical planning questions before investing in managed EV charging programs.
- Where is EV adoption most likely to occur, and where will localized load growth create the greatest planning challenges?
- Which managed EV charging technologies provide the best balance of communications capabilities, implementation costs, and operational flexibility?
- How much can managed EV charging reduce future G&T coincident peak demand charges while maintaining customer participation?
- Will a managed EV charging program produce a positive financial return while supporting increasing EV electricity sales?
GIM Model Resources
Managed EV Charging Planning and Distribution Analysis
The Grid Impact Model helps electric cooperatives move from recognizing that EV adoption is growing to making informed decisions about how to manage it. By combining localized EV forecasting with business case analysis, the model identifies where distribution impacts are most likely to occur, evaluates alternative managed charging strategies, and quantifies the operational and financial benefits of different implementation approaches.
Localized Grid Impact Planning
- Identify neighborhoods, block groups, and feeders where EV adoption is expected to create the greatest localized load growth.
- Forecast the timing and magnitude of future EV charging impacts.
- Evaluate weather-sensitive peak loading under unmanaged and managed charging scenarios.
- Support long-term distribution planning using localized hourly load forecasts.
- Evaluate opportunities for non-wires alternatives and distributed energy resources.
- Provide planning information for capital budgeting and board presentations.
Managed EV Charging Business Case Analysis
- Compare alternative managed EV charging communications and control technologies, including meter collars, AMI-based solutions, and vehicle telematics.
- Compare implementation costs, communications capabilities, and operational flexibility.
- Estimate reductions in G&T coincident peak demand charges.
- Evaluate alternative customer participation levels and incentive strategies.
- Quantify incremental EV energy sales and resulting utility financial performance.
- Compare lifecycle costs and benefits under alternative program designs.
- Support board and management investment decisions with transparent financial analyses.
Support for Existing Distribution Planning Tools
- Export localized EV load forecasts for use in CYME, Synergi, WindMil, OpenDSS, and other distribution planning tools.
- Map block group and neighborhood forecasts to feeders, transformers, or GIS service territories.
- Compare unmanaged and managed EV charging scenarios in existing engineering studies.
- Prioritize feeder and transformer studies based on projected EV growth hotspots.
- Incorporate localized hourly load shapes into time-series analyses.
- Combine EV forecasts with existing demand response assumptions.
- Screen potential infrastructure impacts before detailed circuit modeling.
Grid Impact Model Resource FAQ
What Grid Impact Model resources are available?
Available resources include a summary introduction, a 1-minute executive video, an online viewer presentation, a primary Grid Impact Model web page, an example model session, and related notes on EV load forecasting, customer digital twins, and neighborhood load impacts.
Who is this resource page intended for?
The page is intended for utility executives, distribution planners, engineering consultants, DSM and DER program managers, and others evaluating EV load growth, electrification, and localized grid impacts.
How do these resources support EV load forecasting?
The linked materials explain how the Grid Impact Model forecasts localized EV adoption and hourly charging loads at ZIP, block group, neighborhood, and customer levels.
How do these resources support non-wires alternatives planning?
The resources show how DSM, DER, managed charging, and VPP strategies can be evaluated as options for reducing or shifting local loads before capital upgrades are required.