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Title: On the spatial decorrelation of stochastic solar resource variability at long timescales

Abstract

Understanding the spatial and temporal characteristics of solar resource variability is important because it helps inform the discussion surrounding the merits of geographic dispersion and subsequent electrical interconnection of photovoltaics as part of a portfolio of future solutions for coping with this variability. The unpredictable resource variability arising from the stochastic nature of meteorological phenomena (from the passage of clouds to the movement of weather systems) is of most concern for achieving high PV penetration because unlike the passage of seasons or the shift from day to night, the uncertainty makes planning a challenge. A suitable proxy for unpredictable solar resource variability at any given location is the series of variations in the clearness index from one time period to the next because the clearness index is largely independent of the predictable influence of solar geometry. At timescales shorter than one day, the correlation between these variations in clearness index at pairs of distinct geographic locations decreases with spatial extent and with timescale. As the aggregate variability across N decorrelated locations decreases as 1/√N, identifying the distance required to achieve this decorrelation is critical to quantifying the expected reduction in variability from geographic dispersion.

Authors:
 [1];  [2]
  1. Columbia Univ., New York, NY (United States)
  2. Columbia Univ., New York, NY (United States); Brookhaven National Lab. (BNL), Upton, NY (United States)
Publication Date:
Research Org.:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1221757
Report Number(s):
BNL-108386-2015-JA
Journal ID: ISSN 0038-092X; YN0100000
Grant/Contract Number:  
DGE-1144155
Resource Type:
Accepted Manuscript
Journal Name:
Solar Energy
Additional Journal Information:
Journal Volume: 117; Journal Issue: C; Journal ID: ISSN 0038-092X
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY

Citation Formats

Perez, Marc J. R., and Fthenakis, Vasilis M.. On the spatial decorrelation of stochastic solar resource variability at long timescales. United States: N. p., 2015. Web. doi:10.1016/j.solener.2015.04.020.
Perez, Marc J. R., & Fthenakis, Vasilis M.. On the spatial decorrelation of stochastic solar resource variability at long timescales. United States. https://doi.org/10.1016/j.solener.2015.04.020
Perez, Marc J. R., and Fthenakis, Vasilis M.. Sat . "On the spatial decorrelation of stochastic solar resource variability at long timescales". United States. https://doi.org/10.1016/j.solener.2015.04.020. https://www.osti.gov/servlets/purl/1221757.
@article{osti_1221757,
title = {On the spatial decorrelation of stochastic solar resource variability at long timescales},
author = {Perez, Marc J. R. and Fthenakis, Vasilis M.},
abstractNote = {Understanding the spatial and temporal characteristics of solar resource variability is important because it helps inform the discussion surrounding the merits of geographic dispersion and subsequent electrical interconnection of photovoltaics as part of a portfolio of future solutions for coping with this variability. The unpredictable resource variability arising from the stochastic nature of meteorological phenomena (from the passage of clouds to the movement of weather systems) is of most concern for achieving high PV penetration because unlike the passage of seasons or the shift from day to night, the uncertainty makes planning a challenge. A suitable proxy for unpredictable solar resource variability at any given location is the series of variations in the clearness index from one time period to the next because the clearness index is largely independent of the predictable influence of solar geometry. At timescales shorter than one day, the correlation between these variations in clearness index at pairs of distinct geographic locations decreases with spatial extent and with timescale. As the aggregate variability across N decorrelated locations decreases as 1/√N, identifying the distance required to achieve this decorrelation is critical to quantifying the expected reduction in variability from geographic dispersion.},
doi = {10.1016/j.solener.2015.04.020},
journal = {Solar Energy},
number = C,
volume = 117,
place = {United States},
year = {Sat May 16 00:00:00 EDT 2015},
month = {Sat May 16 00:00:00 EDT 2015}
}

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