Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Try the next-generation Data Catalog at catalog-beta.data.gov and help shape it with your feedback.

  • Feedback

    • Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption

    Metadata Updated: April 16, 2025

    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 advanced metering infrastructure (AMI) devices and phasor measurement units (PMUs) in order to accommodate extreme levels of PV. For this goal, we aim at creating a highly efficient AI framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse AMI devices and PMUs. The files contain the integrated bad data detection with a pre-trained Deep Neural Network-based State Estimation (DNN-SE) model with a voltage regulation control algorithm to manage over-voltage issues in J-1 Feeder with high PV penetration.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: Creative Commons Attribution

    Downloads & Resources

    Dates

    Metadata Created Date April 16, 2025
    Metadata Updated Date April 16, 2025

    Metadata Source

    Harvested from OpenEI data.json

    Other Data Resources

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date April 16, 2025
    Metadata Updated Date April 16, 2025
    Publisher Arizona State University
    Maintainer
    Identifier https://data.openei.org/submissions/8345
    Data First Published 2025-02-01T07:00:00Z
    Data Last Modified 2025-04-16T21:08:50Z
    Public Access Level public
    Bureau Code 019:20
    Metadata Context https://openei.org/data.json
    Metadata Catalog ID https://openei.org/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Data Quality True
    Harvest Object Id 30a5c51b-ceb8-46cc-8abf-791ecee14ac1
    Harvest Source Id 7cbf9085-0290-4e9f-bec1-91653baeddfd
    Harvest Source Title OpenEI data.json
    Homepage URL https://data.openei.org/submissions/8345
    License https://creativecommons.org/licenses/by/4.0/
    Old Spatial {"type":"Polygon","coordinates":-127.91233750000005,23.94630673589783,-66.5318,23.94630673589783,-66.5318,49.2637,-127.91233750000005,49.2637,-127.91233750000005,23.94630673589783}
    Program Code 019:000, 019:008
    Projectnumber EE0009355
    Projecttitle Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption
    Source Datajson Identifier True
    Source Hash 359bc133d49f782addbe50a577fb0d399cf15699905808c8e6ce136046e7a7fa
    Source Schema Version 1.1
    Spatial {"type":"Polygon","coordinates":-127.91233750000005,23.94630673589783,-66.5318,23.94630673589783,-66.5318,49.2637,-127.91233750000005,49.2637,-127.91233750000005,23.94630673589783}

    Didn't find what you're looking for? Suggest a dataset here.