Electric Vehicle Charging Emissions – Good and Better?

AutoInformed.com on WattTime Automated Emissions Reduction Software

Click to Enlarge. See text for electric power utilities studied in chart.

It’s a simple problem with potentially complex answers and political sub-problems. If EVs are the future of automobility because they pollute less than internal combustion cars, how much do they pollute when recharging? A new report from WattTime* explores the question and offers Automated Emissions Reduction software as a solution. It is in AutoInformed’s view a closely reasoned – albeit self-interested – argument that is devoid of the usual hype, omissions and prevarications of many EV producers and actors.

The number of electric vehicles (EVS) on U.S. roadways allegedly will grow from 1 million in 2018 to nearly 19 million in 2030. In tandem, electric vehicle charging points are also expected to increase, including nearly 10 million level 2 charging stations distributed across homes, offices, and public locations.

Level 2 chargers in WattTime’s view are “especially ripe for optimization-price, emissions, or other-since an EV’s charge duration is typically shorter than the overall charge window.”

The Grid

As more renewable energy gets added to traditionally fossil-fueled power grids, real-time emissions rates are increasingly exhibiting large swings from clean to dirty and vice versa from one moment to the next. This is a well-known and classic EV problem. They are in fact Elsewhere Emissions Vehicles.

EVs in theory can become cleaner, by optimizing charging to sync with clean energy and avoid dirty energy. However, effectively implementing this requires accurate data on which times are cleaner and software that can control the EVs to prioritize charging at these times. WattTime refers to a successfully implemented complete package of all the necessary components of emissions-optimized electricity use (including as used for EV charging in its report’s analysis) as Automated Emissions Reduction (AER).

WattTime claims to see a growing number of periods of surplus renewable energy going to waste. Charging an EV at these exact moments causes no incremental pollution at all, because it simply absorbs surplus renewable energy that otherwise would have gone to waste. This opens up the possibility of EVs that could charge on 100% renewable energy, at least at times, even on grids that still have some fossil-fueled generation as part of their mix.

This report’s analysis claims to answer two questions:

  1. How much cleaner can EVs be with correctly implemented emissions-optimized charging?
  2. What would be the collective environmental impact of emissions-optimized charging given 2030 EV adoption forecasts and widespread adoption?

WattTime analyzed the additional, incremental emissions reductions that could be achieved with emissions- optimized charging vs. baseline EV charging. It considered average and high mileage scenarios for two of the most common EV charging profiles (i.e., daytime workplace charging, overnight at-home charging). It examined four representative grids that cover a spectrum of fossil fuel and renewable energy generation mixes:

  • California Independent System Operator (CAISO) northern California subregion,
  • New York Independent System Operator (NYISO) NYC subregion,
  • Southwest Power Pool (SPP), and
  • Western Area Power Administration Rocky Mountain Region (WACM).


Smarter charging reduces Annual emissions up to an additional 18%. While all EVs—even those charged on dirty grids—are cleaner than the average internal combustion engine auto, emissions-optimized charging makes them even cleaner still (by up to 18% vs. baseline charging). Emissions-optimized smart charging reduces EVS’ per-mile emissions intensity, equivalent to giving them up to a 10 MPGe “boost.”

Smarter charging reduces DAILY emissions up to an additional 90%. Because some days experience more emissions variability than others, emissions-optimized EV charging can achieve significant additional emissions reductions vs. baseline on select days. In addition to helping maximize overall total annual emissions reductions, such daily opportunities can help address regional air quality concerns on alert days and aid renewable energy grid integration during times of excessive curtailment and surplus renewable generation.

Emissions reductions are possible everywhere.

WattTime found emissions-reduction opportunities in a variety of U.S. geographies, although the biggest opportunities are in “blended” grids (i.e., fossil and renewable generation) that exhibit large emissions-rate swings. Charging protocols well-matched to the local generation mix (e.g., overnight charging in wind-rich SPP, daytime charging in sun-rich CAISO) maximize emissions reductions.

Adopted at scale, emissions-optimized EV charging could yield very large aggregate, absolute emissions reductions. For example, deployed across California’s target of 5 million zero-emissions vehicles (ZEV) by 2030, emissions-optimized EV charging could achieve the emissions-reduction equivalent of taking more than 180,000 gasoline-burning international combustion engine (ICE) cars off the road. These emissions savings are incremental above and beyond emissions savings of baseline EV charging vs. tailpipe emissions from internal combustion engine (ICE) autos. Similarly, with New York’s target of 2 million EVs by 2030, smarter charging could yield incremental additional savings equivalent to taking nearly 48,000 ICE cars off the state’s roadways.

Thoughtful rate design is critical to align EV charging incentives—and should complement emissions- optimized EV charging. As EV-specific and overall time- of-use (TOU) rates and demand charges become more prevalent nationwide, thoughtful rate design will be helpful to ensure that price signals align with emissions intensity.

However, even when prices and emissions rates do align, the vast majority of all rate structures still lack the granularity necessary to take advantage of short-term swings in emissions, which can often account for the lion’s share of possible emissions savings. Thus, automated software like emissions-optimized EV charging that also intelligently av

Executive Summary

Three trends are rapidly converging:

  1. Accelerating electric vehicle adoption in the United States,
  2. The growth of smart, level 2 EV charging, and
  3. Increasingly variable grid emissions rates thanks to renewable energy additions to traditionally fossil-fueled grids.

WattTime claims the timing is right to integrate time-based marginal emissions signals into EV charging protocols. Doing so can help make clean EVs even cleaner, help states, and utilities achieve policy goals (e.g., battery energy storage, climate, emissions), respond to consumer motivations and demand for green lifestyle options, and aid further renewable energy grid integration.


WattTime is a 501(c)3 software tech startup, “dedicated to giving everyone everywhere the power to choose clean energy.” It claims to have invented the Automated Emissions Reduction (AER), which allows loT devices—smart thermostats, battery energy storage, electric vehicles, and more—as well as the utilities and people that use them, to effortlessly reduce emissions from energy, when and where they happen.

AER works by deploying insights and algorithms, coupled with machine learning, to shift the timing of flexible electricity use to sync with times of cleaner energy and avoid times of dirtier energy. WattTime conducts ongoing research collaborations into the algorithms and analyses that make AER possible, advocates for the spread of AER, and assists organizations in adopting the technology by selling software “to achieve emissions reductions without compromising cost and user experience.” WattTime was founded by PhD students at the University of California, Berkeley, and in 2017 became a subsidiary of Rocky Mountain Institute.

About Kenneth Zino

Ken Zino is an auto industry veteran with global experience in print, broadcast and electronic media. He has auto testing, marketing, public relations and communications expertise garnered while working in Asia, Europe and the U.S.
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