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Repositorio de la Universidad de Oviedo. > Producción Bibliográfica de UniOvi: RECOPILA > Artículos >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/30251

Title: Missing data imputation of solar radiation data under different atmospheric conditions
Author(s): Crespo Turrado, María Concepción
López, M. C. M.
Sánchez Lasheras, Fernando
Gómez, B. A. R.
Rollé, J. L. C.
Cos Juez, Francisco Javier de
Issue date: 2014
Publisher: MDPI
Publisher version: http://dx.doi.org/10.3390/s141120382
Citation: Sensors (Switzerland), 14(11), p. 20382-20399 (2014); doi:10.3390/s141120382
Format extent: p. 20382-20399
Abstract: Global solar broadband irradiance on a planar surface is measured at weather stations by pyranometers. In the case of the present research, solar radiation values from nine meteorological stations of the MeteoGalicia real-time observational network, captured and stored every ten minutes, are considered. In this kind of record, the lack of data and/or the presence of wrong values adversely affects any time series study. Consequently, when this occurs, a data imputation process must be performed in order to replace missing data with estimated values. This paper aims to evaluate the multivariate imputation of ten-minute scale data by means of the chained equations method (MICE). This method allows the network itself to impute the missing or wrong data of a solar radiation sensor, by using either all or just a group of the measurements of the remaining sensors. Very good results have been obtained with the MICE method in comparison with other methods employed in this field such as Inverse Distance Weighting (IDW) and Multiple Linear Regression (MLR). The average RMSE value of the predictions for the MICE algorithm was 13.37% while that for the MLR it was 28.19%, and 31.68% for the IDW
URI: http://hdl.handle.net/10651/30251
ISSN: 1424-8220
Sponsored: Francisco Javier de Cos Juez and Fernando Sánchez Lasheras appreciate support from the Spanish Economics and Competitiveness Ministry, through grant AYA2010-18513
Project id.: MINECO/AYA2010-18513
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