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Title: Characterizing local high-frequency solar variability and its impact to distribution studies

Abstract

Accurately representing the local solar variability at timescales relevant to distribution grid operations (30-seconds and shorter) is essential to modeling the impact of solar photovoltaics (PV) on distribution feeders. Due to a lack of available high-frequency solar data, some distribution grid studies have used synthetically-created PV variability or measured PV variability from a different location than their study location. In this work, we show the importance of using accurate solar PV variability inputs in distribution studies. Using high-frequency solar irradiance data from 10 locations in the United States, we compare the ramp rate distributions at the different locations, use a quantitative metric to describe the solar variability, and run distribution simulations using representative 1-week samples from each location to determine the impact of solar variability on the number of tap change operations. Results indicate up to a 300% difference in the number of tap change operations when using PV variability profiles from the different locations.

Authors:
 [1];  [2];  [2]
+ Show Author Affiliations
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States); Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
OSTI Identifier:
1497655
Report Number(s):
SAND-2014-16368J
Journal ID: ISSN 0038-092X; 672037
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Accepted Manuscript
Journal Name:
Solar Energy
Additional Journal Information:
Journal Volume: 118; Journal Issue: C; Journal ID: ISSN 0038-092X
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; Solar variability; Distribution grid integration; Voltage regulator; Tap changes

Citation Formats

Lave, Matthew Samuel, Reno, Matthew J., and Broderick, Robert Joseph. Characterizing local high-frequency solar variability and its impact to distribution studies. United States: N. p., 2015. Web. doi:10.1016/j.solener.2015.05.028.
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Lave, Matthew Samuel, Reno, Matthew J., & Broderick, Robert Joseph. Characterizing local high-frequency solar variability and its impact to distribution studies. United States. https://doi.org/10.1016/j.solener.2015.05.028
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Lave, Matthew Samuel, Reno, Matthew J., and Broderick, Robert Joseph. Thu . "Characterizing local high-frequency solar variability and its impact to distribution studies". United States. https://doi.org/10.1016/j.solener.2015.05.028. https://www.osti.gov/servlets/purl/1497655.
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@article{osti_1497655,
title = {Characterizing local high-frequency solar variability and its impact to distribution studies},
author = {Lave, Matthew Samuel and Reno, Matthew J. and Broderick, Robert Joseph},
abstractNote = {Accurately representing the local solar variability at timescales relevant to distribution grid operations (30-seconds and shorter) is essential to modeling the impact of solar photovoltaics (PV) on distribution feeders. Due to a lack of available high-frequency solar data, some distribution grid studies have used synthetically-created PV variability or measured PV variability from a different location than their study location. In this work, we show the importance of using accurate solar PV variability inputs in distribution studies. Using high-frequency solar irradiance data from 10 locations in the United States, we compare the ramp rate distributions at the different locations, use a quantitative metric to describe the solar variability, and run distribution simulations using representative 1-week samples from each location to determine the impact of solar variability on the number of tap change operations. Results indicate up to a 300% difference in the number of tap change operations when using PV variability profiles from the different locations.},
doi = {10.1016/j.solener.2015.05.028},
journal = {Solar Energy},
number = C,
volume = 118,
place = {United States},
year = {2015},
month = {6}
}
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Journal Article:
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Publisher's Version of Record
https://doi.org/10.1016/j.solener.2015.05.028
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Figures / Tables:

Figure 1 Figure 1: Map of high-frequency data.
All figures and tables (14 total)
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Works referenced in this record:

Impact of high PV penetration on voltage regulation in electrical distribution systems
conference, June 2011

Analysis of the Impacts of Distribution Connected PV Using High-Speed Datasets
conference, April 2013

  • Bank, Jason; Mather, Barry
  • 2013 IEEE Green Technologies Conference (GreenTech 2013), 2013 IEEE Green Technologies Conference (GreenTech)
  • DOI: 10.1109/GreenTech.2013.31

Modeling Smart Grid Applications with Co-Simulation
conference, October 2010

  • Godfrey, Tim; Mullen, Sara; Griffith, David W.
  • 2010 1st IEEE International Conference on Smart Grid Communications (SmartGridComm), 2010 First IEEE International Conference on Smart Grid Communications
  • DOI: 10.1109/SMARTGRID.2010.5622057

Initial operating experience of the 1.2-MW La Ola photovoltaic system
conference, June 2012

  • Johnson, Jay; Schenkman, Benjamin; Ellis, Abraham
  • 2012 IEEE 38th Photovoltaic Specialists Conference (PVSC) PART 2
  • DOI: 10.1109/PVSC-Vol2.2012.6656701

High-frequency irradiance fluctuations and geographic smoothing
journal, August 2012

Short-term irradiance variability: Preliminary estimation of station pair correlation as a function of distance
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Detailed grid integration analysis of distributed PV
conference, June 2012

  • Quiroz, Jimmy; Reno, Matthew
  • 2012 IEEE 38th Photovoltaic Specialists Conference (PVSC), 2012 38th IEEE Photovoltaic Specialists Conference
  • DOI: 10.1109/PVSC.2012.6317683

Time series simulation of voltage regulation device control modes
conference, June 2013

  • Quiroz, Jimmy E.; Reno, Matthew J.; Broderick, Robert J.
  • 2013 IEEE 39th Photovoltaic Specialists Conference (PVSC)
  • DOI: 10.1109/PVSC.2013.6744472

Voltage Fluctuations on Distribution Level Introduced by Photovoltaic Systems
journal, March 2006

  • Woyte, A.; Thong, V. V.; Belmans, R.
  • IEEE Transactions on Energy Conversion, Vol. 21, Issue 1
  • DOI: 10.1109/TEC.2005.845454

Fluctuations in instantaneous clearness index: Analysis and statistics
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      Figures / Tables found in this record:

      Figure 1 (p. 2)figure
      Table 1 (p. 2)table
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      Figure 11 (p. 8)figure
      Figure 12 (p. 9)figure
      Figure 13 (p. 9)figure
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