The research, published Sept. 24 in the journal Risk Analysis, was led by the University at Buffalo and Purdue University. 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.

Roshanak Nateghi, assistant professor of industrial engineering and environmental and ecological engineering, is a co-author of the study. "The availability of public data in the energy sector, combined with advances in algorithmic modeling, has enabled us to go beyond existing approaches that often exhibit poor predictive performance," she says. "As a result, we're able to better characterize the nexus between energy demand and climate change, and assess future supply inadequacy risks."

The study's lead author is Sayanti Mukherjee, assistant professor of industrial and systems engineering in University of Buffalo's School of Engineering and Applied Sciences.