How Will Climate Change Stress the Power Grid?

How Will Climate Change Stress the Power Grid?

Hint: Look at Dew Point Temperatures

A new study by Sayanti Mukherjee, an assistant professor in the Department of Industrial and Systems Engineering, suggests the power industry is underestimating how climate change could affect the long-term demand for electricity in the United States. It describes the limitations of prediction models used by electricity providers and regulators for medium- and long-term energy forecasting. And it outlines a new model that includes key climate predictors — mean dew point temperature and extreme maximum temperature — that researchers say present a more accurate view of how climate change will alter future electricity demands.

“Existing energy demand models haven’t kept pace with our increasing knowledge of how the climate is changing,” says Mukherjee. “This is troublesome because it could lead to supply inadequacy risks that cause more power outages, which can affect everything from national security and the digital economy to public health and the environment.”

Existing energy demand models haven't kept pace with our increasing knowledge of how the climate is changing.

—Sayanti Mukherjee Assistant professor of industrial and systems engineering

Limitations of Existing Models

One of the most common energy modeling platforms used to predict future electricity demand — MARKAL, named after MARKet and ALlocation — does not consider climate variability. Another common energy-economic model, the National Energy Modeling System (NEMS), does consider the climate; however, it is limited to heating and cooling degree days.

While there are different ways to measure heating and cooling degree days, they are most often calculated by adding the day’s high and low temperature, and then dividing the sum by two. The trouble with this approach is that it doesn’t consider time. For example, it could be 76 degrees for 23 hours and 60 degrees for one hour — yet the average temperature that day would still be recorded as 68 degrees.

Dew Point Temperature is the Key

To address these limitations, the researchers studied more than a dozen weather measurements. They found that the mean dew point temperature — the temperature at which air is saturated with water vapor — is the best predictor of increased energy demand. The next best predictor was the extreme maximum temperature for a month.

The researchers combined these climate predictors with three other categories — the sector (residential, commercial and industrial) consuming the energy, weather data and socioeconomic data — to create their model. They applied the model to the state of Ohio and found that the residential sector is most sensitive to climate variabilities. With a moderate rise in dew point temperature, electricity demand could increase up to 20%. The prediction jumps to 40% with a severe rise.

By comparison, the Public Utility Commission of Ohio (PUCO), which does not consider climate change in its models, predicts residential demand increases of less than 4% up to 2033. The situation is similar for the commercial sector, where demand could increase to 14%. Again, PUCO’s projections are lower, 3.2%. The industrial sector is less sensitive to temperature variability; however, researchers say the demand could still exceed projections.

While the study is limited to Ohio, researchers say the model can be applied to other states.

The research was published in the journal Risk Analysis and was funded in part by the Purdue Climate Change Research Center and the National Science Foundation.

— CORY NEALON