An Approach for Data Treatment of Solar Photovoltaic Generation
| Autor: | A.C.G. Melo, José Francisco Moreira Pessanha, Djalma M. Falcão, Roberto Caldas |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
General Computer Science Computer science business.industry Group method of data handling 020209 energy Photovoltaic system Irradiance 02 engineering and technology Solar energy 01 natural sciences Data modeling Outlier 0202 electrical engineering electronic engineering information engineering ComputerSystemsOrganization_SPECIAL-PURPOSEANDAPPLICATION-BASEDSYSTEMS Electrical and Electronic Engineering Time series business Solar power 0105 earth and related environmental sciences Remote sensing |
| Zdroj: | IEEE Latin America Transactions. 18:1563-1571 |
| ISSN: | 1548-0992 |
| Popis: | A good solar power photovoltaic generation forecast depends on good quality time series data from measurements of Global Horizontal Irradiance and Solar Power Generation. However, measurement system failures and errors in data handling can corrupt data records with gaps and outliers that undermine forecasting accuracy. Therefore, it is important that the fitting of solar energy prediction models must be preceded by a data analysis in order to detect and correct measurement errors. Given that Global Horizontal Irradiance and Solar Power Generation are correlated variables, this paper aims to present the main characteristics of an offline approach developed for the joint treatment of hourly data values of both variables in a photovoltaic plant. In the proposed methodology, the measurements of Global Horizontal Irradiance and Solar Power Generation are analyzed by using reanalysis data and statistical and data mining techniques for the correction of outliers and the filling of data gaps. The application of the approach is illustrated by the analysis of measurements from a real solar PV system. |
| Databáze: | OpenAIRE |
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