Decarbonization pathways for the New York state's electric power sector are investigated using a novel multiscale bottom-up optimization framework coupled with machine learning, showing that expanding electricity storage capacities can reduce the total decarbonization transition costs and facilitate intermittent renewable energy applications.
Systems Ph.D. student Ning Zhao and Systems field member Fengqi You, the Roxanne E. and Michael J. Zak Professor, had their research featured on the cover of ACS Sustainable Chemistry & Engineering with artwork by Rob Kurcoba, graphic designer for Cornell Engineering.
The article, "Toward Carbon-Neutral Electric Power Systems in the New York State: a Novel Multi-Scale Bottom-Up Optimization Framework Coupled with Machine Learning for Capacity Planning at Hourly Resolution," appears in the February 7 issue of the journal, and concludes that "expanding electricity storage capacities can reduce the total decarbonization transition costs and facilitate intermittent renewable energy applications (including wind and solar). It can lead to 39% higher total generation capacity in the New York State; without it, 200% more non-intermittent energy-based generation capacity is required."
For more on the article, please see ACS Sustainable Chemistry & Engineering, Vol. 10, Issue 5.
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