Grid-Edge resource controller to enhance distribution grid resilience [SWR-19-70]

Abstract

This Grid-Edge resource controller provides an unprecedented operational resilience enhancement solution for distribution grids to achieve the lowest system degradation and fast service restoration during extreme events. Specifically, it involves integrated planning and operation approaches that provide distribution grids with a self-evolving capability on dynamically altering system topology and adjusting the operations of edge-intelligent resources in response to dynamic weather disruptions.
Developers:
Ding, Fei [1] Liu, Weijia [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Release Date:
2019-10-09
Project Type:
Closed Source
Software Type:
Scientific
Programming Languages:
Python
Sponsoring Org.:
Code ID:
123216
Site Accession Number:
NREL SWR-19-70
Research Org.:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Country of Origin:
United States

Citation Formats

Ding, Fei, and Liu, Weijia. Grid-Edge resource controller to enhance distribution grid resilience [SWR-19-70]. Computer Software. USDOE Laboratory Directed Research and Development (LDRD) Program. 09 Oct. 2019. Web. doi:10.11578/dc.20240301.1.
Ding, Fei, & Liu, Weijia. (2019, October 09). Grid-Edge resource controller to enhance distribution grid resilience [SWR-19-70]. [Computer software]. https://doi.org/10.11578/dc.20240301.1.
Ding, Fei, and Liu, Weijia. "Grid-Edge resource controller to enhance distribution grid resilience [SWR-19-70]." Computer software. October 09, 2019. https://doi.org/10.11578/dc.20240301.1.
@misc{ doecode_123216,
title = {Grid-Edge resource controller to enhance distribution grid resilience [SWR-19-70]},
author = {Ding, Fei and Liu, Weijia},
abstractNote = {This Grid-Edge resource controller provides an unprecedented operational resilience enhancement solution for distribution grids to achieve the lowest system degradation and fast service restoration during extreme events. Specifically, it involves integrated planning and operation approaches that provide distribution grids with a self-evolving capability on dynamically altering system topology and adjusting the operations of edge-intelligent resources in response to dynamic weather disruptions.},
doi = {10.11578/dc.20240301.1},
url = {https://doi.org/10.11578/dc.20240301.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240301.1}},
year = {2019},
month = {oct}
}