Electricity

Electricity is produced from energy sources such as wind and solar energy, hydropower, nuclear energy, stored hydrogen, oil, coal, and natural gas. It is defined as an alternative fuel by the Energy Policy Act of 1992 (DOE, 2019). For additional background, see the Alternative Fuels Data Center's Electricity Basics webpage.

On this page, explore the fuel price and emissions intensity of electricity.

Emissions estimates use the Argonne National Laboratory's Research & Development Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model (Wang et al., 2023). The underlying source for a value in the table can be seen by placing your mouse cursor over that value. The data sources are also cited—with linked references—in the Key Assumptions section next.

Key Assumptions

The data and estimates presented here are based on the following key assumptions:

• Fuel Price: The fuel price is associated with a single year. Because we do not provide a time-series trajectory, here we show fuel price at a frozen level for all years so we can offer a range of fuel price values. In the levelized cost of driving (LCOD) and emissions charts, this approach clearly distinguishes effects of fuels from those of vehicle technologies because fuels remain constant whereas vehicle technologies change over time.
• Fuel Price Composition: The fuel price for electricity is intended to reflect the retail price to the consumer, less taxes, and includes the wholesale production cost and the cost of infrastructure for electricity delivery and vehicle charging. We do not include taxes on electricity for transportation use because electricity for transportation use is not currently taxed. 
• Charging and Grid Mix Scenarios: Multiple charging and grid mix scenarios are provided, which are meant to encompass the potential variability of charging types, electricity prices, and emissions.

In both the light-duty plug-in electric vehicles (LD PEV) and medium-and-heavy-duty plug-in electric vehicle (MHD PEV) scenarios:

• Electricity prices represent both electricity rates and levelized cost of charging infrastructure. Rates are estimated from the various references for grid mixes, described next, and charging infrastructure cost adders are estimated using the Electric Vehicle Infrastructure – Financial Analysis Scenario (EVI-FAST) model (NREL, 2023).
• For charging infrastructure cost adders, estimates were developed for various vehicles applications for LD PEV (residential, public/commercial, public direct current fast charging [DCFC]) and MHD PEV (depot, corridor). Equipment and infrastructure costs include on-site charging equipment and associated financing, installation, maintenance, operation, and local distribution grid upgrade costs. Assumptions are documented next.

In the LD PEV charging scenarios:

• The electricity price represents an estimate of the average price paid by a current LD PEV user, inclusive of both electricity rates and levelized cost of charging infrastructure. 
• This price is a weighted average of different electricity rates and charging infrastructure costs, meant to reflect a national average. We assume 81% of LD PEV charging happens at home (Borlaug et al., 2020) and is paid at the average residential electricity rate. Moreover, electric vehicles are often charged using favorable time-of-use rates, if available, that provide discounted electricity during certain hours of the day (usually at night) and align well with electric vehicle charging needs (Kaluza et al., 2016). We assume 50% of home charging takes advantage of time-of-use rates and these provide a 75% price saving, based on (Borlaug et al., 2020). Residential charging infrastructure costs are a mix of 16% Level 1 (L1) and 84% Level 2 (L2) (Borlaug et al., 2020). We assume the remaining 19% of charging happens at public stations, for which costs and business models are variable. We assume 14% of charging is at workplaces or community chargers and 5% of PEV charging is en route at direct current fast chargers (Borlaug et al., 2020). For public charging, we assume average commercial rates associated with the included grid mix scenarios and charging infrastructure costs as documented next. We note the current charging mix assumptions are based on near-term charging behavior (primarily home charging) and may not be reflective of future scenarios with widespread adoption of electric vehicles (EVs) with a higher share of EV owners that do not have access to residential charging but instead rely solely on public or workplace charging. 
• The charging price estimated on the ATB are intended to represent national weighted average values across all households and considering a mix of charging applications, rather than where PEVs are currently located and how the charging applications are adopted today. The following table summarizes the share of charging applications for LD PEV charging and the costs associated with the PEV Charging, National Grid Mix scenario.

Charging Cost and Scenario Assumptions for Current LD PEV Charging

• The additional LD PEV charging high-cost case is included to explore the sensitivity of LD LCOD to electricity price. The high-cost case represents a scenario with no time-of-use rates. The price is calculated using the home, workplace, and public charging shares above (with no time-of-use rates).
• The additional LD DCFC scenario is based on the estimated price of DCFC of using commercial rates and only DCFC infrastructure costs. The higher cost assumptions are used as an upper bound on national average electricity prices.
• The additional Future Charging scenarios assume charging infrastructure cost reductions consistent with the low range of values in (Wood et al., 2023).
• Input assumptions to EVI-FAST are documented in the following table (NREL, 2023).Charging Infrastructure Cost Assumptions for LD PEV Charging

In the MHD PEV charging scenarios:

• The electricity price represents an estimate of the average price paid by MHD PEV users, inclusive of both electricity rates and levelized costs of charging infrastructure. These charging scenarios incorporate cost estimates of infrastructure for depot and corridor charging applications, as low and high bounds, respectively, including varying assumptions on charging power and utilization. 
• We represent MHD PEV charging costs as ranges because of the large variability and uncertainty in the use of alternative fueling infrastructure for MHD PEV applications. The resulting range for current charging cost adders reflects a range of applications and assumptions, summarized in the following table.

Charging Cost and Scenario Assumptions for Current MDHD PEV Charging

• The above cost range has been generalized to represent the cost of charging any MHD PEV, but the specific cost of charging a particular MHD PEV can vary greatly, depending on the different charging needs and strategies for different MHD vehicles. Though some pickup trucks and vans may charge in ways and costs similar to LD vehicles in terms of power level and dwell locations and dwell periods, other trucks may charge at higher power levels or at different frequencies and durations and/or rely on dedicated chargers with low utilization. 
• The additional Future Charging scenarios assume charging infrastructure cost adders based on infrastructure capital and installation cost reductions aligned with the low end of values from (Wood et al., 2023).
• Input assumptions to EVI-FAST are documented in the following table (NREL, 2023).Charging Infrastructure Cost Assumptions for LD PEV Charging

In the varied grid mix scenarios:

• For current grid mix scenarios (National, Indiana [IN], and California [CA]) residential and commercial electricity prices are estimated from 2020 average electricity retail price data from the U.S. Energy Information Administration (EIA) (EIA, 2023a). The grid mixes for the national and Indiana and California grid mix scenarios are based on 2020 state-level electricity generation from EIA (EIA, 2023b). These states are selected to illustrate a range of state-level emissions; emissions for each state are beyond the current Annual Technology Baseline (ATB) data scope.
• The Future National Grid Mix and Future Low Renewable Energy Penetration scenarios are based on 2050 values in the Annual Energy Outlook 2023 for the Reference and High Zero-Carbon Technology Cost cases, respectively (EIA, 2023c). The Future High Renewable Energy Penetration scenario is estimated from the 2050 results of the Low Renewable Energy Cost scenario in the 2022 NREL Standard Scenarios analysis (Gagnon et al., 2024), with use of rates from (EIA, 2023c) for consistency. The Standard Scenario analysis provides only wholesale electricity prices; therefore, we apply the percent change in wholesale prices for 2020–2050 to the 2020 residential and commercial rates from the Annual Energy Outlook 2023 Reference case to estimate electricity prices for the Future High Renewable Energy Penetration scenario.
• The emissions intensities are estimated using the Research & Development Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model (Wang et al., 2023) and are based on grid mixes corresponding to each scenario described above. The following table shows the generation penetration by technology for each grid mix scenario (numbers may not sum to 100% because of rounding).

Electricity Mix by Technology for Alternative Grid Mix Scenario

• Electricity losses related to charging are included in the vehicle fuel economy estimates.
• The electricity price is converted to dollars per gasoline gallon equivalent from dollars per kilowatt-hour, assuming 1 gallon gasoline equivalent (gge) = 33.7 kilowatt-hours (EPA, 2011).

The data downloads include additional details of assumptions and calculations for each metric.

Definitions

For detailed definitions, see:

CO2e

NOx

SOx

PM

Electricity

Fuel price

Natural gas

Scenarios

Well-to-tank emissions

References

The following references are specific to this page; for all references in this ATB, see References.