Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations

By strategically curtailing active power and providing reactive power support, photovoltaic (PV) systems with advanced inverters can mitigate voltage and thermal violations in distribution networks. Quasi-static time-series (QSTS) simulations are increasingly being utilized to study the implementati...

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Main Authors: Joseph A. Azzolini, Matthew J. Reno, Nicholas S. Gurule, Kelsey A. W. Horowitz
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Open Access Journal of Power and Energy
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9537896/
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spelling doaj-31ec182bcd6846e1bf0e6ce8ce3f5a122021-09-27T23:01:06ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102021-01-01836537610.1109/OAJPE.2021.31118219537896Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series SimulationsJoseph A. Azzolini0https://orcid.org/0000-0001-9580-4156Matthew J. Reno1https://orcid.org/0000-0002-4885-0480Nicholas S. Gurule2https://orcid.org/0000-0002-3097-2244Kelsey A. W. Horowitz3https://orcid.org/0000-0002-6431-6931Sandia National Laboratories, Electric Power Systems Research Group, Albuquerque, NM, USASandia National Laboratories, Electric Power Systems Research Group, Albuquerque, NM, USASandia National Laboratories, Renewable and Distributed Systems Integration Group, Albuquerque, NM, USANational Renewable Energy Laboratory, Power Systems Engineering Center, Golden, CO, USABy strategically curtailing active power and providing reactive power support, photovoltaic (PV) systems with advanced inverters can mitigate voltage and thermal violations in distribution networks. Quasi-static time-series (QSTS) simulations are increasingly being utilized to study the implementation of these inverter functions as alternatives to traditional circuit upgrades. However, QSTS analyses can yield significantly different results based on the availability and resolution of input data and other modeling considerations. In this paper, we quantified the uncertainty of QSTS-based curtailment evaluations for two different grid-support functions (autonomous Volt-Var and centralized PV curtailment for preventing reverse power conditions) through extensive sensitivity analyses and hardware testing. We found that Volt-Var curtailment evaluations were most sensitive to poor inverter convergence (−56.4%), PV time-series data (−18.4% to +16.5%), QSTS resolution (−15.7%), and inverter modeling uncertainty (+14.7%), while the centralized control case was most sensitive to load modeling (−26.5% to +21.4%) and PV time-series data (−6.0% to +12.4%). These findings provide valuable insights for improving the reliability and accuracy of QSTS analyses for evaluating curtailment and other PV impact studies.https://ieeexplore.ieee.org/document/9537896/Advanced inverterautonomous volt-varcurtailmentdistribution system analysisPV grid integrationquasi-static time-series
collection DOAJ
language English
format Article
sources DOAJ
author Joseph A. Azzolini
Matthew J. Reno
Nicholas S. Gurule
Kelsey A. W. Horowitz
spellingShingle Joseph A. Azzolini
Matthew J. Reno
Nicholas S. Gurule
Kelsey A. W. Horowitz
Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations
IEEE Open Access Journal of Power and Energy
Advanced inverter
autonomous volt-var
curtailment
distribution system analysis
PV grid integration
quasi-static time-series
author_facet Joseph A. Azzolini
Matthew J. Reno
Nicholas S. Gurule
Kelsey A. W. Horowitz
author_sort Joseph A. Azzolini
title Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations
title_short Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations
title_full Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations
title_fullStr Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations
title_full_unstemmed Evaluating Distributed PV Curtailment Using Quasi-Static Time-Series Simulations
title_sort evaluating distributed pv curtailment using quasi-static time-series simulations
publisher IEEE
series IEEE Open Access Journal of Power and Energy
issn 2687-7910
publishDate 2021-01-01
description By strategically curtailing active power and providing reactive power support, photovoltaic (PV) systems with advanced inverters can mitigate voltage and thermal violations in distribution networks. Quasi-static time-series (QSTS) simulations are increasingly being utilized to study the implementation of these inverter functions as alternatives to traditional circuit upgrades. However, QSTS analyses can yield significantly different results based on the availability and resolution of input data and other modeling considerations. In this paper, we quantified the uncertainty of QSTS-based curtailment evaluations for two different grid-support functions (autonomous Volt-Var and centralized PV curtailment for preventing reverse power conditions) through extensive sensitivity analyses and hardware testing. We found that Volt-Var curtailment evaluations were most sensitive to poor inverter convergence (−56.4%), PV time-series data (−18.4% to +16.5%), QSTS resolution (−15.7%), and inverter modeling uncertainty (+14.7%), while the centralized control case was most sensitive to load modeling (−26.5% to +21.4%) and PV time-series data (−6.0% to +12.4%). These findings provide valuable insights for improving the reliability and accuracy of QSTS analyses for evaluating curtailment and other PV impact studies.
topic Advanced inverter
autonomous volt-var
curtailment
distribution system analysis
PV grid integration
quasi-static time-series
url https://ieeexplore.ieee.org/document/9537896/
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