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Graph theory and nighttime imagery based microgrid design

Journal Article · · Journal of Renewable and Sustainable Energy
DOI:https://doi.org/10.1063/5.0083188· OSTI ID:1888512
Reducing the duration and frequency of blackouts in remote communities poses an engineering challenge for grid operators. Outage effects can also be mitigated locally through microgrids. This paper develops a systematic procedure to account for these challenges by creating microgrids prioritizing high value assets within vulnerable communities. Nighttime satellite imagery is used to identify vulnerable communities. Using an asset classification and rating system, multi-asset clusters within these communities are prioritized. Infrastructure data, geographic information systems, satellite imagery, and spectral clustering are used to form and rank microgrid candidates. A microgrid sizing algorithm is included to guide through the microgrid design process. Finally, an application of the methodology is presented using real event, location, and asset data.
Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
Federal Emergency Management Agency (FEMA); USDOE National Nuclear Security Administration (NNSA)
Grant/Contract Number:
NA0003525
OSTI ID:
1888512
Report Number(s):
SAND2022-12646J; 709960
Journal Information:
Journal of Renewable and Sustainable Energy, Journal Name: Journal of Renewable and Sustainable Energy Journal Issue: 3 Vol. 14; ISSN 1941-7012
Publisher:
American Institute of Physics (AIP)Copyright Statement
Country of Publication:
United States
Language:
English

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