Please use this identifier to cite or link to this item:
|Title: ||Solar Irradiation Data Processing using estimator MatriceS (SIMS) validated for Portugal (southern Europe)|
|Authors: ||Silva, Hugo G.|
Abreu, Edgar F.M.
|Keywords: ||Solar resource assessment|
Data gap filling
Global horizontal irradiation
|Issue Date: ||2020|
|Citation: ||Solar Irradiation Data Processing using estimator MatriceS (SIMS) validated for Portugal (southern Europe), H.G. Silva, E.F.M. Abreu, F.M. Lopes, A. Cavaco, P. Canhoto, J. Neto, M. Collares-Pereira, Renewable Energies, 147(1), 515-528 (2020). DOI: 10.1016/j.renene.2019.09.009|
|Abstract: ||Accurate solar resource assessment is essential in all the different phases of solar energy systems design and implementation. On a local scale, the solar resource is best assessed from ground measurements and, if available, with the existence of complete time-series of hourly values for the long-term resource estimation. However, these usually suffer from the occurrence of data gaps that can be as large as several months for remote and/or less maintained stations. Such gaps hinder the correct assessment of solar availability and, for that matter, their filling is a crucial first step to perform an appropriate assessment. In this context, a method for Solar Irradiation Data Processing using estimator MatriceS (SIMS) has been developed and is presented here. The algorithm allows to determine long-term linear correlations between a network of spatially distributed stations and, with these, to identify possible outliers and to fill data gaps through the selection of the median value from the obtained estimations. The method is validated against global horizontal irradiation (GHI) data from a network that comprises 89 ground measuring stations, being maintained by the Portuguese Meteorology Service (IPMA - Instituto Portugu^es do Mar e da Atmosfera), considering a period of 17 years (from 2001 to 2017). Two important assertions are made for coefficients between stations: (1) coefficients only decrease slightly with the distance between stations (with a median reduction of ~0.0003 km 1), for the considered network; (2) asymptotic long-term coefficients are reached with only one year of data. Taking advantage of the SIMS method, GHI assessment is presented here in the form of availability maps over the Portuguese mainland, with the respective values being listed in a table for future reference. The present assessment confirms that Portugal is a suitable region for the implementation of solar energy systems, with GHI having availabilities up to 2028.4 kWh/m2/year ±3.4% in Sagres (southernmost part of Portugal).|
|Appears in Collections:||FIS - Comunicações - Em Congressos Científicos Internacionais|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.