WITH ONE researchers are developing a new model of EV emissions to quantify the impact of vehicle charging models and ambient temperature on EV emissions levels.
Emissions related to transportation are increasing globally. Today, light vehicles (i.e., passenger cars, such as warmers, SUVs, or minivans) account for about 20% of U.S. greenhouse gas emissions. Studies have shown that shutting down cars that emit conventional gas due to a vehicle equipped with electricity can cause a lot of pollution when it comes to reducing these emissions.
Recent research published in Environmental Science and Technology it goes a step further by examining how to reduce emissions related to the source of electricity used to charge an electric vehicle (EV). Considering the impact of regional charging patterns and ambient temperature on the car’s fuel economy, researchers at the MIT Energy Initiative (MITEI) have found that the time of day an EV is charged has a significant impact on vehicle emissions.
“If you ease the load at certain times, you can encourage reductions in emissions from renewable energy and EV growth,” says Ian Miller, lead author of the research and MITEI research association. “So how do we do this? The usage time for electricity rates is expanding and EV drivers can change the time of day they charge tremendously. We inform politicians of the large impact of charging time, then they can design electricity tariffs when our electricity grids are renewable to discount the charge. In regions with heavy sunshine, it is noon. In regions with heavy winds, such as the Midwest, it’s night. “
According to a study conducted in California, which is a heavy solar, charging an electric vehicle overnight generates 70 percent more emissions than if it were charged at noon (when more solar energy strengthens the electrical grid). Meanwhile, in New York, where nuclear and hydroelectric power make up the bulk of the electrical mix overnight, the best charging time is reversed. In this region, charging the vehicle overnight actually reduces emissions by 20% compared to daytime charging.
“Charging infrastructure is another important determinant when it comes to facilitating loading at specific times, especially during the day,” added Emre Gençer, author and researcher at MITEI. “If you need to charge your car at noon, you need to have enough charging stations in your workplace. Today, most people charge their vehicles in garages overnight, which will create higher emissions in places where charging is better during the day.”
In the study, Miller, Gençer, and Maryam Arbabzadeh, a postdoctoral fellow at MITEI, made some of these observations by calculating the percentage of errors in two common EV emission modeling approaches, excluding variations in lattice time and changes in fuel temperature. economy. The results show that the combined error of these standard methods exceeds 10 percent in 30 percent of cases, and reaches 50 percent in California, which accounts for half of the U.S. EV.
“If you don’t model the charging time and charge it with an average annual power, you can miscalculate EV emissions,” says Arbabzadeh. “Sure, it’s more good to use that solar network and more electric vehicles. It doesn’t matter when you charge your EV in the US, emissions will be lower than similar gasoline-powered cars; when you use it you will get as much profit as you think when it comes to reducing emissions “.
In an effort to reduce the margin of error, the researchers use 2018 and 2019 hourly network data – along with hourly load, driving, and temperature data – to calculate EV usage emissions in 60 U.S. cases. They then present and validate a new method (with a margin of error of less than 1 percent) to accurately calculate EV emissions. They call it the “average day” method.
“We’ve found that you can ignore the seasons in grid emissions and fuel economy, and yet you can accurately calculate annual EV emissions and charging time impacts,” Miller says. “It was a pleasant surprise. In Kansas last year, daily grid emissions rose about 80 percent between seasons, and demand for EV power rose about 50 percent due to temperature changes. Previous research has speculated that not seeing the ups and downs of the season would hurt accuracy EV emission estimates, but the error has never really been quantified. We did it – through a mixture of networks and different climates – and we saw that the mistake was negligible. “
This finding has useful implications for modeling future EV emission scenarios. “You can achieve accuracy without computational complexity,” says Arbabzadeh. “With the average daily method, you can accurately calculate EV emissions and charging effects in the next year without having to simulate 8,760 network emissions values per hour per year. All you need is a single average daily profile, which is only 24-hour values for network emissions and for other key variables. You don’t need to know the seasonal variance of these average day profiles. “
The researchers demonstrate the usefulness of the average daily method by conducting a case study in the southeastern United States to examine how renewable growth in this region may affect future EV emissions from 2018 to 2032. Assuming a conservative projection of the U.S. Energy Information Network, the results show that EV emissions drop by only 16 percent overnight from one charge, but more than 50 percent if the charge occurs at noon. In 2032, compared to a similar hybrid car, EV emissions per kilometer are 30 percent lower if they are charged at night and 65 percent lower if they are charged at noon.
The model used in this study is a module in a larger modeling program called the Sustainable Energy Systems Analysis Modeling Environment (SESAME). This tool, developed at MITEI, takes a systems-wide approach to assessing the full carbon footprint of the current global development system.
“The idea behind SESAME is to make better decisions about decarbonization and to understand the energy transition from a systems perspective,” says Gençer. “One of the key elements of SESAME is how you can link different sectors together -‘ sector coupling ’- and in this study we are looking at a very interesting example of the transport and electricity sectors. Right now, as we have claimed, it is impossible to treat these two sectoral systems independently, and this is clear to show why the vision of MITEI’s new models is so important, as well as how we can address some of these upcoming issues. “
In ongoing and future research, the team is expanding load analysis from individual vehicles to the entire fleet of passenger cars to develop fleet-level decarbonization strategies. Their work seeks to answer questions such as how California’s proposal to sell gasoline cars in 2035 would affect transportation emissions. They are also looking at what the fleet’s electrification means – not only for greenhouse gases, but also the demand for natural resources like cobalt – and are looking at whether EV batteries can have significant grid energy storage.
“To mitigate climate change, we need to decarbonize the transportation and electricity sectors,” says Gençer. “We can electrify transportation and significantly reduce emissions, but what this document shows is how you can do it more efficiently.”
Reference: “Variations in the current grid, models for charging electric vehicles and operating emissions” Ian Miller, Maryam Arbabzadeh and Emre Gençer, November 26, 2020, Environmental Science and Technology.
DOI: 10.1021 / acs.est.0c02312
This research has been promoted by ExxonMobil Research and Engineering through the MIT Energy Initiative, through the Low Carbon Energy Centers.