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This content will become publicly available on March 1, 2017

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:
 [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:
OSTI Identifier:
1115287
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 Laboratories (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