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An advanced statistical method for wind power forecasting

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dc.contributor.author Sideratos, G en
dc.contributor.author Hatziargyriou, ND en
dc.date.accessioned 2014-03-01T01:25:53Z
dc.date.available 2014-03-01T01:25:53Z
dc.date.issued 2007 en
dc.identifier.issn 0885-8950 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/17791
dc.subject Fuzzy sets en
dc.subject Radial base function networks en
dc.subject Self- organized map en
dc.subject Wind power forecasting en
dc.subject.classification Engineering, Electrical & Electronic en
dc.subject.other Artificial intelligence en
dc.subject.other Electric power generation en
dc.subject.other Electric power measurement en
dc.subject.other Fuzzy sets en
dc.subject.other Radial basis function networks en
dc.subject.other Self organizing maps en
dc.subject.other Weather forecasting en
dc.subject.other Operational planning en
dc.subject.other Wind farm en
dc.subject.other Wind speed en
dc.subject.other Wind power en
dc.title An advanced statistical method for wind power forecasting en
heal.type journalArticle en
heal.identifier.primary 10.1109/TPWRS.2006.889078 en
heal.identifier.secondary http://dx.doi.org/10.1109/TPWRS.2006.889078 en
heal.language English en
heal.publicationDate 2007 en
heal.abstract This paper presents an advanced statistical method for wind power forecasting based on artificial intelligence techniques. The method requires as input past power measurements and meteorological forecasts of wind speed and direction interpolated at the site of the wind farm. A self-organized map is trained to classify the forecasted local wind speed provided by the meteorological services. A unique feature of the method is that following a preliminary wind power prediction, it provides an estimation of the quality of the meteorological forecasts that is subsequently used to improve predictions. The proposed method is suitable for operational planning of power systems with increased wind power penetration, i.e., forecasting horizon of 48 h ahead and for wind farm operators trading in electricity markets. Application of the forecasting method on the power production of an actual wind farm shows the validity of the method. © 2007 IEEE. en
heal.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC en
heal.journalName IEEE Transactions on Power Systems en
dc.identifier.doi 10.1109/TPWRS.2006.889078 en
dc.identifier.isi ISI:000243914400029 en
dc.identifier.volume 22 en
dc.identifier.issue 1 en
dc.identifier.spage 258 en
dc.identifier.epage 265 en


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