Evaluation of Horizon of Viability Optimization Engine for Sustained Power to Critical Infrastructure

Vivek Khatana, Soham Chakraborty, Govind Saraswat, Blake Lundstorm, Murti V. Salapaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In the aftermath of increasingly frequent catastrophic events, a typical scenario is critical infrastructure (CI) units being supported by available backup sources with a weak power grid that can be intermittent or absent. Such a scenario is significantly challenging in the sense of providing reliable supply of power to CI units. In this article, an intelligent optimization scheme, termed a horizon of viability (HoV) engine, is developed to guarantee the viability of a sustained, reliable supply of power to the CI units over a time horizon. The proposed HoV engine generates a cost-optimal portfolio of the locally available generation sources and the loads over a time horizon using a mixed-integer convex programming problem. A controller-hardware-in-the-loop (CHIL) platform is developed to evaluate the control performance of the HoV engine. The experimental results corroborate the efficacy in maintaining the viability of the CI units after a grid interruption event. Further, the proposed HoV optimization scheme performs better than existing net-load management schemes in the literature.

Original languageEnglish (US)
Title of host publication2022 IEEE Power and Energy Conference at Illinois, PECI 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665402293
DOIs
StatePublished - 2022
Event2022 IEEE Power and Energy Conference at Illinois, PECI 2022 - Champaign, United States
Duration: Mar 10 2022Mar 11 2022

Publication series

Name2022 IEEE Power and Energy Conference at Illinois, PECI 2022

Conference

Conference2022 IEEE Power and Energy Conference at Illinois, PECI 2022
Country/TerritoryUnited States
CityChampaign
Period3/10/223/11/22

Bibliographical note

Funding Information:
The authors acknowledge the Advanced Research Projects Agency-Energy (ARPA-E) for supporting this research through the project titled "Rapidly Viable Sustained Grid" via grant no. DE-AR0001016. This work was authored in part by the National Renewable Energy Laboratory, managed and operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.

Funding Information:
The authors acknowledge the Advanced Research Projects Agency-Energy (ARPA-E) for supporting this research through the project titled “Rapidly Viable Sustained Grid” via grant no. DE-AR0001016. This work was authored in part by the National Renewable Energy Laboratory, managed and operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. The views expressed in the article do not necessarily represent the views of the DOE or the U.S. Government. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes.

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Disaster resiliency
  • generation scheduling
  • load management
  • microgrid
  • mixed-integer programming

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