In the United States, electricity generation accounts for nearly 30% of our carbon emissions. Some states have responded to that by setting aggressive renewable energy standards; others are hoping to see coal propped up even as its economics get worse. Complicating matters further is the fact that many regional grids are integrated, meaning power generated in one location may be exported and used in a different state entirely.
Tracking these electricity exports is critical for understanding how to lower our national carbon emissions. In addition, power from a dirty source like coal has health and environment impacts where it’s produced, and the costs of these aren’t always paid by the parties using the electricity. Unfortunately, getting reliable figures on how electricity is produced and where it’s used is challenging, leaving some of the best estimates with a time resolution of only a month.
Now, three Stanford researchers—Jacques A. de Chalendar, John Taggart, and Sally M. Benson—have greatly improved on that standard, and they have managed to track power generation and use on an hourly basis. The researchers found that, of the 66 grid balancing areas within the United States, only three have carbon emissions equivalent to our national average, and they have found that imports and exports of electricity have both seasonal and daily changes. de Chalendar et al. discovered that the net results can be substantial, with imported electricity increasing California’s emissions/power by 20%.
Hour by hour
To figure out the US energy trading landscape, the researchers obtained 2016 data for grid features called balancing areas. The continental US has 66 of these, providing much better spatial resolution on the data than the larger grid subdivisions. This doesn’t cover everything—several balancing areas in Canada and Mexico are tied in to the US grid—and some of these balancing areas are much larger than others. The PJM grid, serving Pennsylvania, New Jersey, and Maryland, for example, is more than twice as large as Texas’ ERCOT.
Despite these limitations, it’s possible to get hourly figures on how much electricity was generated, what was used to produce it, and whether it was used locally or exported to another balancing area. Information on the generating sources allowed the researchers to attach an emissions figure to each unit of electricity produced. Coal, for example, produces double the emissions of natural gas, which in turn produces more than an order of magnitude more carbon dioxide than the manufacturing of solar, wind, or hydro facilities. These figures were turned into what the authors call “embodied emissions” that can be traced to where they’re eventually used.
Similar figures were also generated for sulfur dioxide and nitrogen oxides. Released by the burning of fossil fuels, these can both influence the global climate and produce local health problems.
The results were striking. “The consumption-based carbon intensity of electricity varies by almost an order of magnitude across the different regions in the US electricity system,” the authors conclude. The low is the Bonneville Power grid region, which is largely supplied by hydropower; it has typical emissions below 100kg of carbon dioxide per megawatt-hour. The highest emissions come in the Ohio Valley Electric region, where emissions clear 900kg/MW-hr. Only three regional grids match the overall grid emissions intensity, although that includes the very large PJM, ERCOT, and Southern Co balancing areas.
Most of the low-emissions power that’s exported comes from the Pacific Northwest’s abundant hydropower, while the Rocky Mountains area exports electricity with the highest associated emissions. That leads to some striking asymmetries. Local generation in the hydro-rich Idaho Power Company has embodied emissions of only 71kg/MW-hr, while its imports, coming primarily from Rocky Mountain states, have a carbon content of 625kg/MW-hr.
The reliance on hydropower also makes the asymmetry seasonal. Local generation is highest in the spring as snow melts, but imports become a larger source outside this time of year. As solar and wind can also have pronounced seasonal shifts, similar changes will likely be seen as these become larger contributors to many of these regional grids. Similar things occur daily, as both demand and solar production (and, to a lesser extent, wind) have distinct daily profiles.
The Golden State
California’s CISO provides another instructive case. Imports represent less than 30% of its total electric use in 2016 but provided 40% of its embodied emissions. Some of these, however, come internally from California, provided by the Los Angeles Department of Water and Power. The state itself, however, has only had limited tracking of imported emissions, lumping many of its sources as “other.”
Overall, the 2016 inventory provides a narrow picture of the US grid, as plenty of trends are rapidly changing our country’s emissions profile, including the rise of renewables and the widespread adoption of efficiency measures. The method developed here can, however, allow for annual updates, providing us with a much better picture of trends. That could be quite valuable to track things like how the rapid rise in solar power is altering the daily production of clean power.
More significantly, it provides a basis for more informed policymaking. States that wish to promote low-emissions power can use the information here to either alter the source of their imports or to encourage the sites where they’re produced to adopt more renewable power. And those states that are exporting electricity produced primarily through fossil fuels could ensure that the locations where the power is used pay a price that includes the health costs of its production.