Quasi-Static Time-Series PV Hosting Capacity Methodology and Metrics

Akshay Kumar Jain, Kelsey Horowitz, Fei Ding, Barry Mather, Bryan Palmintier, Nicolas Gensollen

Research output: Contribution to conferencePaperpeer-review

31 Scopus Citations

Abstract

Distributed photovoltaic systems (DPV) can cause adverse grid impacts, including voltage or thermal violations. The installed capacity at which violations first occur and above which would require system upgrades is called the hosting capacity. Current methods for determining hosting capacity tend to be conservative by either only considering infrequent worst-case snapshots in time and/or only capturing coarse time and spatial resolution. Additionally, current hosting capacity methods do not accurately capture the time-dependence making them unable to capture the behavior of voltage regulating equipment and of some advanced controls mitigations. This can trigger delays from unnecessary engineering analysis or deter solar installations in areas that are actually suitable. We propose a quasi-static-time-series (QSTS) based PV hosting capacity methodology to address these issues. With this approach, we conduct power flow analysis over the course of a full year, to capture time-varying parameters and control device actions explicitly. We show that this approach can more fully capture grid impacts of DPV than traditional methods.

Original languageAmerican English
Number of pages5
DOIs
StatePublished - Feb 2019
Event2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019 - Washington, United States
Duration: 18 Feb 201921 Feb 2019

Conference

Conference2019 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2019
Country/TerritoryUnited States
CityWashington
Period18/02/1921/02/19

Bibliographical note

See NREL/CP-5D00-72284 for preprint

NREL Publication Number

  • NREL/CP-5D00-74935

Keywords

  • PV Hosting Capacity
  • Quasi-Static Time-Series Simulation
  • System Impact Studies

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