Stanford Energy is brought to you by the Precourt Institute for Energy
By Mark Shwartz
About 30 percent of U.S. greenhouse gas emissions come from power plants that generate electricity by burning fossil fuels. Now, Stanford University scientists have developed a new way to track those emissions on an hour-by-hour basis across the entire electric grid.
This novel approach will provide grid operators and electricity consumers a precise tool for reducing carbon dioxide and other emissions in real time, according to the study published this week in the Proceedings of the National Academy of Sciences.
“If we want to get serious about curbing carbon emissions, we need to measure them with precision,” said PhD student Jacques de Chalendar, lead author of the study. “Looking at data at the hourly level, instead of monthly or yearly as is typically done, is a much more targeted way to accurately assess and control emissions.”
A power plant in Arizona (Credit: U.S. Department of State)
The new tool will also enable grid operators to quickly evaluate the carbon intensity of electricity imports, said study co-author Sally Benson, co-director of Stanford’s Precourt Institute for Energy and professor of energy resources engineering in the School of Earth, Energy & Environmental Sciences.
“If you know the time of day when carbon intensity is high, you can choose to purchase energy from regions with cleaner power,” said Benson. “That’s important because, as we look to the future, we’re likely to see a more interconnected grid nationwide.”
The electric grid that powers the continental United States consists of 66 balancing authorities – regional control centers responsible for matching electricity supply and demand 24 hours a day, seven days a week.
For the study, the Stanford team calculated hourly consumption and emissions for all 66 authorities during 2016 using public data from the U.S. Environmental Protection Agency and the Energy Information Administration.
The largest authority – the Pennsylvania-New Jersey-Maryland Power Pool (PJM) – consumed 20 percent of U.S. electricity and generated 19 percent of total power-plant emissions that year.
But a more refined analysis revealed significant fluctuations depending on the time of day and the season. The study found that consumption and emissions in PJM were greatest in the late afternoon on hot summer days and in early fall.
“When you track emissions, you need to see what’s happening every hour of the day and night,” said de Chalendar. “Without that time granularity, you’re missing a big part of the picture.”
Balancing authorities routinely import and export electricity to meet regional energy demands, particularly in the western United States.
“People assume that their electricity comes from close-by, but in reality the U.S. grid is one big, interconnected machine, where power generated in one place is often consumed elsewhere,” explained de Chalendar.
But electricity consumption on one end of the grid can cause emissions of CO2 and noxious air pollutants hundreds of miles away, he added.
“Some places get all the emissions from generating electricity but not the power,” he said. “People in those regions often bear a disproportionate air-pollution burden.”
One of the country’s biggest electricity importers is the California Independent System Operator, a balancing authority that managed 84 percent of the state’s electricity consumption in 2016. That same year, imports accounted for 28 percent of CalISO’s electricity consumption and 40 percent of its CO2 emissions.
The control room of the California Independent System Operator (Credit: California ISO)
The study found that for California’s five largest balancing areas, including CalISO, imports represented about 30 percent of CO2 emissions. But all of the CO2 and associated air pollution from those imports was actually released outside of California in states like Arizona that produce electricity from coal and natural gas, then export power to the West Coast.
Overall, 17 percent of total CO2 emissions in the Western grid were generated to satisfy electrical consumption in a different region.
Emissions also varied significantly at different times of the year. “For CalISO, we estimated that, in the fall, the median hourly carbon intensity of imports is 394 kilograms of CO2 per megawatt-hour,” said Benson. “But in the springtime, it drops to 216 kg/MWh. That’s significantly lower.”
Understanding seasonal variations will have a direct impact on exporting states. But tracking the source of these emissions in real time will also be critical for California if the state is to meet its target of 100 percent carbon-free electric power by 2045, said Benson.
“One way for California to achieve that ambitious goal is by importing clean electricity,” she said “But that will require CalISO and the other balancing authorities to continuously monitor the grid to make sure they’re actually purchasing clean power from other states.”
Having precise data to untangle this complex flow of carbon is essential for policymakers hoping to address climate change, de Chalendar added.
“States that consume imported electricity should take responsibility for exporting emissions, but this problem can’t by solved by individual states alone,” he said. “People from different parts of the grid should be in the room as part of the conversation. At some point, you have to start thinking at the regional or federal level.”
The new tool will also give big corporations a more rigorous way to monitor electricity use and reduce their carbon footprint, said de Chalendar.
“Companies will be able to look at how much electricity they’re consuming, and how emission-intensive that power is, every hour of the year,” he said. “That will enable them to shift their operations scheduling to better match the carbon-intensity of the grid.”
Until now, policymakers would sometimes have to make assumptions about the carbon intensity of imports with little data, said Benson
“Now they have a very technical, mathematical approach that has practical implications,” she said. “Jacques is working on making this tool accessible in real time 24/7 using publicly available data sets.”
The study was also co-authored by John Taggart, a PhD student in management science and engineering.