Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies
Publicly accessible
License
This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system contingency analyses along with graph and topology measurements under each contingency scenario of the power system.
Citation Formats
NREL. (2020). Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies [data set]. Retrieved from 15613936-fef1-437b-a7c6-335d566e9f3b.
Bush, . Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies. United States: N.p., 01 Aug, 2020. Web. 15613936-fef1-437b-a7c6-335d566e9f3b.
Bush, . Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies. United States. 15613936-fef1-437b-a7c6-335d566e9f3b
Bush, . 2020. "Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies". United States. 15613936-fef1-437b-a7c6-335d566e9f3b.
@div{oedi_6351, title = {Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies}, author = {Bush, .}, abstractNote = {This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system contingency analyses along with graph and topology measurements under each contingency scenario of the power system.}, doi = {}, url = {15613936-fef1-437b-a7c6-335d566e9f3b}, journal = {}, number = , volume = , place = {United States}, year = {2020}, month = {08}}
Details
Data from Aug 1, 2020
Last updated Dec 18, 2024
Submitted Aug 1, 2020
Organization
NREL
Contact
Brian W Bush
