EN عنوان مقاله | Wind power prediction based on wind speed forecast using hidden Markov model |
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نویسندگان | Khatereh Ghasvarian Jahromi, Davood Gharavian, Hamid Reza Mahdiani |
نشریه | Journal of Forecasting |
عنوان لاتين مجله | Journal of Forecasting |
كد DOI/DOR | https://doi.org/10.1002/for.2889 |
ارائه به نام دانشگاه | دانشگاه شهید بهشتی |
شماره صفحات | 2064 |
صفحه پايان | 2087 |
شماره سریال | 43 |
شماره مجلد | 6 |
ضریب تاثیر (IF) | 3.4 |
نوع مقاله | Original Research |
تاریخ انتشار | 14/07/2022 |
رتبه نشریه | ISI |
نوع نشریه | الکترونیکی |
کشور محل چاپ | بریتانیا |
نمایه نشریه | JCR |
چکیده مقاله
This study examines a new approach for short-term wind speed and power forecasting based on the mixture of Gaussian hidden Markov models (MoG-HMMs). The proposed approach focuses on the characteristics of wind speed and power in the consecutive hours of previous days. The proposed method is carried out in two steps. In the first step, for the hourly prediction of wind speed, several wind speed features are employed in MoG-HMM, and in the second step, the results obtained from the first step along with their characteristics and wind power features are used to predict wind power estimation. To increase the prediction accuracy, the data used in each step are classified, and then for each class, one HMM with its specific parameters is used. The performance of the proposed approach is examined using real NREL data. The results show that the proposed method is more precise than other examined methods.
tags: discrete wavelet transform, hidden Markov model, short-term prediction, wind power, wind speed