Evaluation of Weather Information for Short-Term Wind Power Forecasting with Various Types of Models

نویسندگان

چکیده

The rising share of renewable energy in the mix brings with it new challenges such as power curtailment and lack reliable large-scale grid. forecasting wind generation for provision flexibility, defined ability to absorb manage fluctuations demand supply by storing at times surplus releasing when needed, is important. In this study, short-term models were developed using conventional time-series method hybrid support vector regression (SVR) based on rolling origin recalibration. For application methodology, meteorological database from Korea Meteorological Administration actual operating data a turbine (2.3 MW) 1 January 31 December 2015 used. results showed that proposed SVR model has higher accuracy than existing methods. addition, high under proper curation operation data. Therefore, analysis reveal weather information are important forecasting.

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ژورنال

عنوان ژورنال: Energies

سال: 2022

ISSN: ['1996-1073']

DOI: https://doi.org/10.3390/en15249403