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Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption
The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse AMI devices and PMUs in order to accommodate extreme levels of PV. For this goal, w...
Ayyanar, R. et al Arizona State University
Feb 01, 2025
2 Resources
0 Stars
In curation
2 Resources
0 Stars
In curation
Distributed Solar Technoeconomic Agent Characteristics dSTAC
These data files summarize key techno-economic metrics used in the NREL dGen model for modeling adoption of distributed solar by representative residential commercial and industrial entities for each county in the continental United States. As described further below many of the m...
Kwasnik and SigrinNational Renewable Energy Laboratory
Feb 07, 2019
51 Resources
0 Stars
Publicly accessible
51 Resources
0 Stars
Publicly accessible