Developed by Energy Infrastructure Partners
Enter your fleet specifications below. The tool generates a grid impact estimate ready for your utility coordination meeting, modeling four load management scenarios so you can partner with your utility to identify infrastructure options that reduce upgrade costs and shorten coordination timelines.
| # | VehicleSelect your WAZIP-eligible vehicle. The catalog contains 47 medium and heavy-duty BEVs across Class 4 through Class 8. | ClassVehicle weight class, automatically populated from your selection. | Daily MilesAverage miles driven per day per vehicle. | Charge StartTime the vehicle plugs in to begin charging. | Charge EndTime the vehicle must be ready for service. | Charger TypeCharger model. The effective charging rate caps at the vehicle's maximum acceptance rate. | Op Days/MoOperating days per month. Default 22 (weekdays only). Range: 1 to 31. | StatusRow status. Green = ready. Gray italic = input missing. Amber = soft warning. Red = error, row excluded from totals. | ActionsDuplicate copies this row into the next empty row. Reset returns this row to defaults. |
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| # | VehicleSelect from the full HVIP/WAZIP catalog of 136 Class 2b through Class 8 BEVs, sorted A-Z. | ClassVehicle weight class, automatically populated from your selection. | Daily MilesAverage miles driven per day per vehicle. | Charge StartTime the vehicle plugs in to begin charging. | Charge EndTime the vehicle must be ready for service. | Charger TypeCharger model. The effective charging rate caps at the vehicle's maximum acceptance rate. | Op Days/MoOperating days per month. Default 22. Range: 1 to 31. | StatusRow status. Green = ready. Gray italic = input missing. Amber = soft warning. Red = error, row excluded from totals. | ActionsDuplicate copies this row into the next empty row. Reset returns this row to defaults. |
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Contact your utility the moment you submit your fleet purchase order, not after delivery. The cost of utility coordination is mostly time. Equipment lead times for utility-owned infrastructure (transformers, switchgear, primary service) range from weeks to multiple years. None of these timelines start until the utility has your service request in hand.
Energy per vehicle: The tool multiplies each vehicle's daily miles by its EPA-rated energy consumption (kWh per mile) to determine how much energy the battery must recover overnight. Vehicle efficiency values are sourced from the WAZIP Vehicle Equipment Catalog v2.
Effective charge rate: A charger's rated output is capped at the vehicle's maximum power acceptance rate. The tool uses whichever is lower.
Fleet peak demand: The theoretical maximum is the sum of effective charge rates across all vehicles — every charger running at full power simultaneously. This is the CF = 1.00 figure.
Coincidence factor scenarios: CF = 0.85 reflects natural arrival stagger with no coordination. CF = 0.70 reflects basic charge scheduling software. CF = 0.50 reflects active demand response.
Infrastructure sizing: Service capacity adds a 25% planning margin to the conservative peak. Transformer size steps up to the next standard ANSI/IEEE nameplate rating above that service capacity.
Annual energy: Monthly consumption is multiplied by 12 to project annual use. This assumes the same number of operating days every month. Actual annual consumption will vary with seasonal routes, scheduled maintenance, and changes to fleet utilization. For budgeting purposes, treat the annual figure as a consistent-schedule baseline rather than a precise forecast.
The coincidence factor (CF) is the ratio of actual simultaneous peak demand to the theoretical maximum if every charger drew full power at the same instant. CF = 1.00 means every vehicle charges at full rate simultaneously.
Most utilities default to CF = 1.00 when sizing infrastructure for an EV fleet. This is conservative planning that almost never matches real fleet behavior. The result is transformer, service, and substation capacity quoted for a peak demand that will never actually occur.
Each row represents one vehicle, mirroring how WAZIP itself accounts for vehicles (per voucher, per VIN). For schedule diversity, give the same vehicle multiple rows with different Charge Start and Charge End values.
WAZIP IM Section 2.3.a caps a Purchaser at 10 active vouchers at one time, with 30 vouchers per biennium. The ten-row architecture for new fleet vehicles mirrors that cap.
Your commercial electricity bill has two separate cost components. The first is the energy charge: a straightforward cost per kilowatt-hour consumed, similar to a household bill. The second is the demand charge, and this is where fleets often get caught off guard.
Your utility measures your single highest 15-minute power draw during the billing month and charges a fee based on that peak. That fee applies for the entire month, whether the spike happened once or every day. So if ten trucks all plug in at the same time on one Tuesday evening and create a 400 kW surge, you pay a demand charge based on 400 kW for the whole month.
Simultaneous EV charging is almost purpose-built to trigger high demand charges. For large fleets, demand charges can account for 30% to 50% of a monthly electricity bill. Understanding this is the starting point for evaluating any load management strategy, because most of the financial benefits from managed charging software and battery buffers flow directly from reducing or eliminating that peak.
Managed charging is software that controls when and how fast each vehicle charges, so your site never draws more power than a set limit. Instead of every truck plugging in and pulling full power at once, the platform staggers and throttles individual chargers automatically. You still get every vehicle fully charged by morning. Your utility sees a much lower peak.
For fleet operators, this has three direct financial benefits. First, it reduces your demand charge by flattening the spike that would otherwise set your monthly peak. Second, if your utility offers time-of-use rates (cheaper electricity during off-peak overnight hours), a managed charging platform can automatically schedule charging to take advantage of those lower rates without any manual coordination. Third, a lower demonstrated peak gives your utility a basis to size your infrastructure to a smaller, less expensive scope than the worst-case assumption, reducing upfront capital cost.
Basic scheduling typically cuts peak draw by 15% to 30% with no hardware changes. More advanced platforms that respond to real-time signals from your utility can reduce your peak by closer to 50%. Most commercial charging station management systems include scheduling as a standard feature, but capabilities vary widely across vendors.
Engaging your utility early, before you take delivery, gives you time to find the right infrastructure fit and explore which charging management options work for your operation, your site, and your budget. Vendors, your utility, and resources like the DOE's FEMP program are all good starting points for that research.
References: Smart Charge Management for Federal Fleets — DOE FEMP | Electric Vehicle Managed Charging — NREL (2022)
A battery buffer is an on-site battery system that charges slowly from the grid overnight and then powers your chargers during the vehicle charging window. Your utility sees a steady, modest draw instead of a large spike. This can significantly reduce the size of the electrical service your utility needs to install.
The most immediate financial benefit is avoiding or deferring a large infrastructure upgrade. Transformer replacements and new primary service installations can run from tens of thousands to several hundred thousand dollars, with lead times of 18 months or more. A battery buffer can allow you to start charging your fleet at a lower initial service size, getting vehicles on the road sooner while permanent infrastructure is planned and funded. In some cases it can eliminate the need for a major upgrade entirely.
On an ongoing basis, the battery buffer continuously reduces your demand charge by preventing the charging spike from ever reaching the grid. NREL analysis finds that a properly sized system can reduce required grid service capacity by 50% to 80%. If your utility offers lower overnight rates, the battery charges during cheap hours and discharges during expensive ones, adding energy cost savings on top of the demand charge reduction.
The tradeoffs are upfront cost for the battery system and some added complexity managing charge schedules. A battery buffer does not eliminate the need to coordinate with your utility. They still need to know your full requirements, and the battery system itself needs to be connected to an appropriate service entrance.
References: Battery-Buffered EV Charging — DriveElectric.gov | The Critical Role of Energy Storage in Fleet Electrification — Wattstor