Détails sur le projet
Description
We propose to investigate the behavior of individual generators to understand major factors impacting electric system reliability under major weather events like the cold front that affected Texas in February 2021. Using a combination of structural economic estimation, optimization, and machine learning, we will develop a new method to simulate market outcomes under counterfactual conditions in electricity markets. This will allow us to evaluate the relative impact that factors like rm strategic behavior, transmission interconnectivity, and increased gas availability, among others, can have to avoid extended blackouts and system crises such as the one experienced by Texas. We will use detailed data on the electricity market of the neighboring MISO South region, which has similar characteristics and is publicly available, and will combine it with a rich dataset on natural gas pipelines that will allow us to study the interaction between the two systems.
Statut | Actif |
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Date de début/de fin réelle | 6/1/21 → … |
Financement
- National Centre for Supercomputing Applications
Keywords
- Inteligencia artificial
- Ciencias ambientales (todo)
Empreinte numérique
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