TODAY’S STUDY: How Clean Are EVs?

Emissions Associated with Electric Vehicle Charging: Impact of Electricity Generation Mix, Charging Infrastructure Availability, and Vehicle Type

Joyce McLaren, John Miller, Eric O’Shaughnessy, Eric Wood, and Evan Shapiro, April 2016 (National Renewable Energy Laboratory)

Abstract

With the aim of reducing greenhouse gas emissions associated with the transportation sector, policymakers are supporting a multitude of measures to increase electric vehicle adoption. The actual amount of emissions reduction electric vehicles provide is dependent on when and where drivers charge the vehicles. This analysis contributes to our understanding of the degree to which a particular electricity grid profile, the vehicle type, and charging patterns impact CO2 emissions from light-duty, plug-in electric vehicles. We present an analysis of anticipated emissions resulting from both battery electric and plug-in hybrid electric vehicles for four charging scenarios and five electricity grid profiles. A scenario that allows drivers to charge electric vehicles at the workplace yields the lowest level of emissions for the majority of electricity grid profiles. However, vehicle emissions are shown to be highly dependent on the percentage of fossil fuels in the grid mix, with different vehicle types and charging scenarios resulting in fewer emissions when the carbon intensity of the grid is above a defined level. Restricting charging to off-peak hours results in higher total emissions for all vehicle types, as compared to other charging scenarios.

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Introduction and Background

With the aim of reducing greenhouse gas emissions associated with the transportation sector, decision makers at the national, state, and local levels are supporting a multitude of policy measures to increase adoption of light-duty electric vehicles (DOE 2015; DeShazo 2015; ICCT 2015; Zhou 2015). The actual emission-reduction benefits associated with plug-in electric vehicles (PEVs) in a specific location are dependent on multiple factors, such as the electricity generation fuel mix, the time of day charging, and the vehicle type. Using a wide variety of methodologies and assumptions, numerous studies have investigated the impact of these different factors on emissions (Hacker 2007; Parks 2007; Anaire 2012; Kelly 2012; RAP/ICCT 2013; Nunes 2014; Tulpule 2014; Nealer 2015; Wood 2015; Jochem 2016).

A 2012 Union of Concerned Scientists (UCS) study concludes that emissions from electric vehicles are less than those of an average conventional vehicle, regardless of mix of fuels used to generate the electricity on which they are charged (Anair 2012). While the authors of the study acknowledge the impact of location and time of day that charging occurs, they do not specifically calculate PEV emissions for different grid mixes, stating:

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Because the hourly variations in emissions intensity are not consistent across regions, times of day, or seasons, it is not practical to develop general consumer guidelines on when the lowest emissions intensity will occur throughout the day. For now, we recommend that EV consumers use their regional grid emissions, averaged over the course of the year, as a guide to estimating their personal EV global warming emissions.

Several studies have quantified the importance of location and time of day when estimating PEV emissions. Tulpule (2013) concludes that day charging with solar-powered charging stations in Ohio could realize CO2 emissions reductions of up to 90% versus home charging during evening hours. Jochem et al. (2015) finds that total life-cycle external costs of PEVs are highly dependent on the electricity mix and the charging strategy employed.

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While a commonly used methodology bases emissions estimates on the annual average electricity generation mix (Hacker 2007), an alternative approach bases calculations on the electricity fuel source that is on the margin (meaning the electricity load that PEVs add to the existing load). 1 Holland et al. (2015) take this approach, finding significant variation in the marginal emissions associated with PEVs in different locations, thus reinforcing the notion that electricity grid mix has a notable impact on emissions. The authors also point out the potential for the transfer of the emissions benefits of EVs from one location to another, as a result of regional electricity imports and exports. Parks et al. (2007) and Denholm et al. (2013) also use the marginal emission methodology. Both studies conclude that the availability of daytime charging increases the percentage of miles that plug-in hybrid electric vehicles (PHEVs) drive on electricity and results in greater petroleum displacement.

The analysis described in this paper investigates the emissions impacts by time of day and charging scenario for five different electricity grid mixes and multiple vehicle types. We investigate both PHEVs and BEVs that are charged using either slow (level 1) or fast (level 2) charging equipment at varying times of day. The electricity grids on which the vehicles are charged differ in their carbon intensities. Each grid is characterized by an hourly generation profile for an entire week. Seasonal variations are not captured because the profiles represent the average fuel mix over the course of a year.

A strength of our methodological approach is the consideration of not only the emissions associated with charging electric vehicles on a particular electricity grid, but also the emissions associated with the non-electric miles driven. This includes the miles that PHEVs drive in gasoline mode, and those trips that battery electric vehicle (BEV) drivers are required to make in a conventional vehicle (CV). As such, we are able to provide a more complete representation of total emissions associated with PEV-owner travel. Including CV emissions enables this analysis to capture the more nuanced story of PEV use…

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Conclusions

This study analyzes the emissions associated with electric vehicles, with consideration to the vehicle type, the carbon intensity of the grid, and the charging infrastructures and patterns employed. It uses a novel methodology that allows us to consider not only the emissions resulting from charging the PEVs, but also the emissions associated with the miles driven on gasoline. The emissions are calculated for a defined set of trips taken by multiple vehicle types, using anticipated 2025 vehicle efficiencies. Our analysis suggests the following conclusions:

• The carbon intensity of the electricity grid has a greater impact on the total emissions associated with electric vehicles than does the charging scenario. However, differences in emissions between charging scenarios are detectable, with advantages of each differing somewhat according to the carbon intensity of the grid.

• Notably, PHEVs yield lower total emissions than BEVs in four of the five grid types. The low-carbon grid is the only case in which BEVs have lower total emissions. This is due to our inclusion of non-electric miles in the calculation of total emissions. PHEVs have a higher mile-per-gallon efficiency and their non-electric miles have a lower carbon intensity than BEV non-electric miles (which are driven in a conventional vehicle).

• Workplace charging results in the greatest percentage of electric miles for both BEVs and PHEVs and consistently results in lower total emissions across all charging scenarios, with exceptions only for high carbon grids.9

• The emissions benefits of workplace charging increase as the carbon intensity of the grid is reduced. Sensitivity analysis indicates that the Workplace charging scenario continues to result in the least emissions, even when the carbon intensity of the grid varies substantially. However, the larger number of electric miles afforded by workplace charging can result in higher total emissions than other charging scenarios on high carbon grids.

• Of the charging scenarios studied, time-restricted charging results in the lowest number of electric miles and the highest level of emissions for most grids and vehicle types.

• Looking across all of the vehicle types, charging scenarios and grids studied, a BEV using time-restricted charging on a high carbon grid results in the highest level of emissions.

• A BEV using workplace charging on a low carbon grid provides the greatest emissions reductions as compared to driving a conventional vehicle.

Resulting policy and technology considerations include:

• Changes in carbon intensity of the grid impact the emissions associated with workplace charging. This supports the notion that encouraging increased renewable energy in combination with increased workplace charging can have a significant impact on emission reductions associated with electric vehicle deployment.

• Based on the assumptions used in this analysis, the wide-spread use of workplace charging could be expected to reduce emissions associated with electric vehicles on grids with an average carbon intensity of less than 1.5 lb CO2/kWh.

• Regions with carbon-intense electrical grids will realize little (or even negative) benefit by switching from home charging to workplace charging. Policies to reduce grid carbon intensity may provide greater value than policies to promote workplace charging.

• Restricting charging to off-peak hours results in higher total emissions associated with PEVs. This is, in part, a consequence of the reduced number of trips that PEV drivers can comfortably make when charging is restricted to off-peak hours. This result suggests that existing policies and utility rate structures that encourage off-peak charging may lead to higher emissions associated with PEVs than policies that support daytime charging. Altering the times that charging restrictions or special PEV charging rates are in place to increase flexibility may reduce the negative impacts of time-restricted charging on emissions. More analysis of the impacts of time-restricted charging on specific electric grids could help to both reduce the grid impacts associated with increased levels of PEV charging as well as maximize emissions reductions.

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