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:
-
- Sandia National Lab. (SNL-CA), Livermore, CA (United States)
- 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.
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
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.
@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}
}
Web of Science
Figures / Tables:

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Figures / Tables found in this record: