Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies

Description

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.

Resources

Name Format Description Link
ZIP file containing the metadata, the power-system graph, and the results of the power-system simulations and graph/topology measurements. Binary ZIP file containing the metadata, the power-system graph, and the results of the power-system simulations and graph/topology measurements. Open resource
ZIP file containing the metadata, the power-system graph, and the results of the power-system simulations and graph/topology measurements. Binary ZIP file containing the metadata, the power-system graph, and the results of the power-system simulations and graph/topology measurements. Open resource

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