A semiparametric spatio-temporal model for solar irradiance data

Joshua D. Patrick, Jane L. Harvill and Clifford W. Hansen

Renewable Energy, 2016, vol. 87, issue P1, 15-30

Abstract: 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. Our results indicate a promising approach for modeling irradiance at high spatial resolution consistent with available ground-based measurements. Such modeling may find application in design, valuation, and operation of fleets of utility-scale photovoltaic power systems.

Keywords: Irradiance; Spatio-temporal model; Nonseparability; Lattice data; Semiparametric time series (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:87:y:2016:i:p1:p:15-30

DOI: 10.1016/j.renene.2015.10.001

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