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
Author:
Affiliation:
1. Systems Engineering, Cornell University, Ithaca, New York 14853, United States
2. Robert Frederick Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14853, United States
Funder
Division of Chemical, Bioengineering, Environmental, and Transport Systems
Publisher
American Chemical Society (ACS)
Subject
Renewable Energy, Sustainability and the Environment,General Chemical Engineering,Environmental Chemistry,General Chemistry
Link
https://pubs.acs.org/doi/pdf/10.1021/acssuschemeng.1c06612
Reference53 articles.
1. UNFCCC. Adoption of the Paris Agreement, 2020. (accessed Mar 10, 2020).
2. Clean grids with current technology
3. New York State Senate. Senate Bill S6599, https://www.nysenate.gov/legislation/bills/2019/s6599 (accessed Jan 3, 2021).
4. Sustainable energy systems: Role of optimization modeling techniques in power generation and supply—A review
5. New York State's 100% renewable electricity transition planning under uncertainty using a data-driven multistage adaptive robust optimization approach with machine-learning
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