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Online Health Monitoring of Photovoltaic Distributed Energy Resources

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Distributed energy resources (DERs), like rooftop solar photovoltaic (PV) systems, contribute to the largest renew-able energy footprint in the US. With the proliferation of PV DERs, and its ever increasing adoption, stable distribution system operation is now highly dependent on the normal operation of PV DERs. The common notion, so far, for PV DERs was to 'set it, and forget it', with inadequate attention directed towards abnormality detection and operational health status monitoring over its deployment tenure. This paper presents an online operational health monitoring approach for PV DERs that integrates process variable estimators (PVEs), residual computation, statistical sequential analysis, and probabilistic health aggregation to monitor operational health of PV DERs. Implementation of these various components for health monitoring of PV DERs is discussed and their individual as well as integrated performance is illustrated through simulation. Various usage for health monitoring of PV DERs is discussed including large-scale PV DERs management, proactive maintenance of PV DER assets and situational awareness.

Original languageEnglish
Title of host publication2022 IEEE Power and Energy Society General Meeting, PESGM 2022
PublisherIEEE Computer Society
ISBN (Electronic)9781665408233
DOIs
StatePublished - 2022
Event2022 IEEE Power and Energy Society General Meeting, PESGM 2022 - Denver, United States
Duration: Jul 17 2022Jul 21 2022

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2022-July
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2022 IEEE Power and Energy Society General Meeting, PESGM 2022
Country/TerritoryUnited States
CityDenver
Period07/17/2207/21/22

Keywords

  • cyber-physical systems
  • distributed energy resources
  • health monitoring
  • photovoltaic systems
  • power distribution systems
  • resilient control
  • statistical analysis

INL Publication Number

  • INL/CON-21-62134
  • 70626

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