| 1 |
Wind power forecasting - A data-driven method along with gated recurrent neural network
Kisvari A, Lin Z, Liu XL
Renewable Energy, 163, 1895, 2021 |
| 2 |
Diagnosis of wind turbine faults with transfer learning algorithms
Chen WQ, Qiu YN, Feng YH, Li Y, Kusiak A
Renewable Energy, 163, 2053, 2021 |
| 3 |
Identifying early defects of wind turbine based on SCADA data and dynamical network marker
Fang RM, Wu ML, Guo XH, Shang RY, Shao PF
Renewable Energy, 154, 625, 2020 |
| 4 |
Blades icing identification model of wind turbines based on SCADA data
Dong XH, Gao D, Li J, Zhang JC, Zheng K
Renewable Energy, 162, 575, 2020 |
| 5 |
Investigation of energy output in mountain wind farm using multiple-units SCADA data
Dai JC, Tan YY, Shen XB
Applied Energy, 239, 225, 2019 |
| 6 |
A novel wind turbine condition monitoring method based on cloud computing
Qian P, Zhang DH, Tian XG, Si YL, Li LB
Renewable Energy, 135, 390, 2019 |
| 7 |
Using high-frequency SCADA data for wind turbine performance monitoring: A sensitivity study
Gonzalez E, Stephen B, Infield D, Melero JJ
Renewable Energy, 131, 841, 2019 |
| 8 |
The data-driven schedule of wind farm power generations and required reserves
Long H, Zhang ZJ, Sun MX, Li YF
Energy, 149, 485, 2018 |
| 9 |
Effect investigation of yaw on wind turbine performance based on SCADA data
Dai JC, Yang X, Hu W, Wen L, Tan YY
Energy, 149, 684, 2018 |
| 10 |
Anomaly detection and fault analysis of wind turbine components based on deep learning network
Zhao HS, Liu HH, Hu WJ, Yan XH
Renewable Energy, 127, 825, 2018 |
