Multi-step wind speed forecasting and Hurst analysis using novel hybrid secondary decomposition approach
Yazarlar (2)
Prof. Dr. Cem EMEKSİZ Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Mustafa Tan Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Energy (Q1) | ||
| Dergi ISSN | 0360-5442 Dergi Bilgileri (2022) | ||
| Dergi Tarandığı Indeksler | SCI-Expanded | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2022 |
| Cilt / Sayı / Sayfa | 238 / 1 / 121764–0 | DOI | 10.1016/j.energy.2021.121764 |
| Makale Linki | http://dx.doi.org/10.1016/j.energy.2021.121764 | ||
| UAK Araştırma Alanları |
Yenilenebilir Enerji Sistemleri
Elektrik Makineleri ve Enerji Dönüşümü
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| Özet |
| Wind speed should be predicted in a sensitive and reliable manner for the effective use of wind energy in wind farms. However, the volatility and non-linearity features of wind make it difficult to do so. Hence, many researchers have focused on the development of reliable prediction models for wind speed. Aimed at this challenge, the present study proposes a hybrid model comprised of Ensemble Empirical Mode Decomposition Adaptive Noise (CEEMDAN), Local Mean Decomposition (LMD), Hurst and Back-propagation Neural Network (BPNN). This model is actualized as follows: First, wind speed time series is decomposed into its sub-components via CEEMDAN technique. The least irregular and unsystematic of the IMFs with the highest frequency obtained as a result of decomposition via CEEMDAN is subject to secondary decomposition using the LMD technique. The obtained components are subject to Hurst … |
| Anahtar Kelimeler |
| Back propagation neural network | Hurst analysis | Hybrid decomposition technique | Local mean decomposition | Wind speed forecasting |
Science Direct
Multi-step wind speed forecasting and Hurst analysis using novel hybrid secondary decomposition approach
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Yöksis | 47 |
| Web of Science | 77 |
| Scopus | 79 |
| Google Scholar | 84 |