Planning for an Electrified Transportation Future: Modeling Charging Curves and Output Capacity

Predictions show there will be over 26 million electric vehicles on U.S. roads by 2030. With rapid electric vehicle (EV) adoption comes a pressing need for hundreds of thousands of DC fast charging (DCFC) ports. These charging stations will be spread across public and private properties and will involve stakeholders including utilities, private corporations, site owners, and customers. Better utilization modeling is crucial for both utilities and site owners, but predicting the peak demand and energy consumption at these multi-port charging stations is no easy feat.

Utilization modeling begins with an understanding of how EV charging works. Each EV has its own unique charging requirements, including maximum kW limitations, bi-directional charging capabilities, and state of charge dependency. Nearly all currently available EV models use a tapered charging curve, which slows down charging speeds as the battery gets closer to being fully charged. As a result, estimating peak demand and keeping charging sites within capacity limits is a complex task requiring more than simply multiplying the maximum capacity of each port by the total number of ports.

The usage and peak demand at charging stations will depend on several factors, such as customer charging habits, location, seasonal changes, and unexpected events such as emergency evacuations. With many variables at play, accurate utilization models that account for the unique characteristics of each EV model are crucial.
To explore this concept, the Smart Electric Power Alliance (SEPA) developed the first of its kind modeling tool to evaluate DCFC load profiles based on vehicle makes and model-specific charging curves. This tool can help energy industry stakeholders understand fast charging demand and plan their infrastructure accordingly.

DCFC Load Profiles

Site utilization can vary widely depending on the time of year, changes in customer charging behaviors, and traffic surges due to nearby events. Figures 1 and 2 depict how simple changes – such as moving from an off-peak tourism season to a high traffic tourism season and introducing a lunchtime spike in customer demand – could influence a site’s utilization and load profile.

Figure 1. Results from Rural Charging Scenario.

Figure 2. Results from Mixed Fleet + Public Usage Charging Scenario.

Load factors and the ratio of peak demand to nameplate capacity (maximum rated output charger capacity) are low and are expected to remain low due to the tapered charge curve of nearly all currently available EV models. Even as vehicle charging curves improve to accept higher peak powers, as long as power remains a function of state of charge, we can expect charging stations to experience peak loads below the nameplate capacity rating.

Implications for the Energy Industry

Planning for DCFC not only includes utilities and site owners but also regulators, government agencies, and emergency services. Public charging stations will replace traditional gas stations and emergency services will need to incorporate EV charging into their plans. Modeling can help regulators and government agencies test the efficacy of their programs and evaluate secondary policy effects.

Data Sharing

More collaboration is necessary between industry partners, utilities, and DCFC site owners. Access to real-world data on load shapes, nameplate load factors, and utilization data will be extremely valuable to utilities and site owners alike. Utilities and site owners can utilize their current charge curves. Original equipment manufacturers (OEMs) should inform utilities as early as possible about changes such as expanding beyond 150-200 kW charge limits or using flat rate charging curves.

Vehicle Charging Curves are Key

Station level load shapes have meaningful implications for DCFC site planning, asset utilization, and upstream utility infrastructure investment. Today station level nameplate load factors and ratio of peak demand to nameplate capacity are low and are expected to remain low for the foreseeable future. Nameplate load factors are the ratio of the average load to the maximum potential load at nameplate capacity. As table 1 and figure 2 show, the nameplate load factor is less than 14% in the typical charging scenarios evaluated in this report and only increases to 22% in the emergency scenarios where sites are used at full capacity (e.g. 100% utilization during time period of interest).

Table 1. Summarized Results.

Figure 3. Scenario Summary – Utilization, Nameplate Load Factor, Peak Demand

Key Recommendations

For Modeling and Forecasting:

• Nameplate load factor is far more important than utilization to utilities. Nameplate load factor and utilization are not interchangeable given current vehicle charging characteristics.
• As long as vehicle load curves remain a function of battery SOC and are not constant for the duration of charging, it is important to differentiate utilization from nameplate load factor.
• Charging behavior (arriving with a low vs. medium SOC) has meaningful implications for nameplate load factor and peak demand.
• Nameplate load factors are likely to remain low even if utilization increases with growing EV adoption.

For Utility Planning:

• Access to real-world data on load shapes, nameplate load factors, and utilization will be extremely valuable to utilities as they plan to serve new EV charging loads.
• Even in the most extreme examples of ten hours of 100% utilization, the current fleet of vehicles did not exceed 1,100 kW for a 10 port system and nameplate load factors never exceeded 25%.
• With the current charging capabilities, charging sites will rarely, if ever, reach their nameplate capacity.
  • In the short-term, utilities may consider planning infrastructure upgrades to accommodate actual peak demands.
  • In the long-term, utilities will need to consider how changes to charging characteristics will affect site utilization, the ability to reach a site’s nameplate capacity, and a site’s impact on the grid.

For Site Owners:

• Customer charging habits can fluctuate throughout the year and cause spikes in a site’s peak demand. Site owners should analyze likely changes in charging at their site throughout the year and prepare for the impact this may have on setting the site’s monthly bill.
• Energy consumption and peak demand will have different impacts on the site’s monthly bill. Managed charging strategies such as staggered charging, on-site battery storage, sharing power across charge ports, and throttling the charge sessions can decrease monthly bills.

Looking ahead

The ideas presented in the report are helpful to demonstrate the importance of differentiating utilization from nameplate load factor. Check out SEPA’s brief series and executive summary that explore our DCFC demand model and highlight implications for site utilization, tariff design, and resilience.