A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks

Abhijeet Sahu, Kumar Utkarsh, Fei Ding

Research output: Contribution to conferencePaperpeer-review

5 Scopus Citations

Abstract

As a result of climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks; thus, the level of proactive preparation of the distribution system to be able to handle severe impacts of extreme weather events represents the system's resilience. One method that distribution system planners can use to prepare for future extreme events is to plan multiple microgrids which can use local generation as much as possible to supply critical loads. But partitioning an existing distribution system such that multiple feasible islands are planned and which are capable of supporting critical loads is still challenging for distribution systems-first, because of the size of the network graph partitioning problem and, second, because of the difficulty in properly formulating the desired attributes of such islands or microgrids. Therefore, this paper presents a genetic algorithm-based approach that facilitates incorporating multiple objectives for grid partitioning by formulating two types of problems-node allocation and edge elimination-and it considers multiple topological and resilience-enhancing objectives. The performance of the proposed genetic algorithm-based approach is numerically evaluated on multiple test systems as well as on a real distribution feeder in Colorado, United States.

Original languageAmerican English
Number of pages5
DOIs
StatePublished - 2022
Event2022 IEEE Power and Energy Society General Meeting, PESGM 2022 - Denver, United States
Duration: 17 Jul 202221 Jul 2022

Conference

Conference2022 IEEE Power and Energy Society General Meeting, PESGM 2022
Country/TerritoryUnited States
CityDenver
Period17/07/2221/07/22

Bibliographical note

See NREL/CP-5D00-80846 for preprint

NREL Publication Number

  • NREL/CP-5D00-84977

Keywords

  • edge elimination
  • genetic algorithm
  • microgrid
  • multi-objective optimization

Fingerprint

Dive into the research topics of 'A Fast and Scalable Genetic Algorithm-Based Approach for Planning of Microgrids in Distribution Networks'. Together they form a unique fingerprint.

Cite this