Robust Microgrid Scheduling with Resiliency Considerations

Guodong Liu, Thomas Ben Ollis, Yichen Zhang, Tao Jiang, Kevin Tomsovic

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

A new microgrid scheduling model with resiliency guaranteed under the risk of both utility failure and prevailing uncertainties of renewable generation and load is proposed in this article. The proposed model minimizes the overall operating cost of the microgrid by efficiently coordinating the power supply from local distributed energy resources and the main grid. The resiliency is ensured by maintaining certain amount of flexibility in local distributed energy resources, which can be quickly deployed to keep the power supply uninterrupted whenever the utility grid suddenly goes down. In addition, the uncertainties of renewable generation and load are captured with the proposed two-stage robust optimization model. By solving the proposed optimization, the solution not only guarantees the resiliency of the microgrid by supporting possible islanding incidents without load interruption, but also ensures robustness against the randomness of renewable generation and load. Results of case studies on a typical microgrid demonstrate the effectiveness of the presented robust microgrid scheduling model.

Original languageEnglish
Article number9171300
Pages (from-to)153169-153182
Number of pages14
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

Funding

This work was supported in part by the UT-Battelle, LLC, through the U.S. Department of Energy, under Contract DE-AC05-00OR22725, in part by the Engineering Research Center Program of the National Science Foundation and the Department of Energy under NSF Award EEC-1041877, and in part by the CURENT Industry Partnership Program.

Keywords

  • Distributed generation
  • microgrid scheduling
  • resiliency
  • robust optimization
  • unintentional islanding

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