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Title: A semiparametric spatio-temporal model for solar irradiance data

Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance at high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.
Authors:
ORCiD logo [1] ;  [2] ;  [3]
  1. Univ. of California, Davis, CA (United States)
  2. Baylor Univ., Waco, TX (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Report Number(s):
SAND-2013-9073J
Journal ID: ISSN 0960-1481; PII: S0960148115303542
Grant/Contract Number:
AC04-94AL85000
Type:
Accepted Manuscript
Journal Name:
Renewable Energy
Additional Journal Information:
Journal Volume: 87; Journal Issue: P1; Journal ID: ISSN 0960-1481
Publisher:
Elsevier
Research Org:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA)
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; irradiance; spatio-temporal model; nonseparability; lattice data; semiparametric time series
OSTI Identifier:
1115287
Alternate Identifier(s):
OSTI ID: 1396757

Patrick, Joshua D., Harvill, Jane L., and Hansen, Clifford W.. A semiparametric spatio-temporal model for solar irradiance data. United States: N. p., Web. doi:10.1016/j.renene.2015.10.001.
Patrick, Joshua D., Harvill, Jane L., & Hansen, Clifford W.. A semiparametric spatio-temporal model for solar irradiance data. United States. doi:10.1016/j.renene.2015.10.001.
Patrick, Joshua D., Harvill, Jane L., and Hansen, Clifford W.. 2016. "A semiparametric spatio-temporal model for solar irradiance data". United States. doi:10.1016/j.renene.2015.10.001. https://www.osti.gov/servlets/purl/1115287.
@article{osti_1115287,
title = {A semiparametric spatio-temporal model for solar irradiance data},
author = {Patrick, Joshua D. and Harvill, Jane L. and Hansen, Clifford W.},
abstractNote = {Here, we evaluate semiparametric spatio-temporal models for global horizontal irradiance at high spatial and temporal resolution. These models represent the spatial domain as a lattice and are capable of predicting irradiance at lattice points, given data measured at other lattice points. Using data from a 1.2 MW PV plant located in Lanai, Hawaii, we show that a semiparametric model can be more accurate than simple interpolation between sensor locations. We investigate spatio-temporal models with separable and nonseparable covariance structures and find no evidence to support assuming a separable covariance structure. These results indicate a promising approach for modeling irradiance at high spatial resolution consistent with available ground-based measurements. Moreover, this kind of modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.},
doi = {10.1016/j.renene.2015.10.001},
journal = {Renewable Energy},
number = P1,
volume = 87,
place = {United States},
year = {2016},
month = {3}
}