| 1 |
Chaotic wind power time series prediction via switching data-driven modes
Ouyang TH, Huang HM, He YS, Tang ZH
Renewable Energy, 145, 270, 2020 |
| 2 |
Advanced wind power prediction based on data-driven error correction
Yan J, Ouyang TH
Energy Conversion and Management, 180, 302, 2019 |
| 3 |
Prediction of wind power ramp events based on residual correction
Ouyang TH, Zha XM, Qin L, He YS, Tang ZH
Renewable Energy, 136, 781, 2019 |
| 4 |
Bread-making synthesis of hierarchically Co@C nanoarchitecture in heteroatom doped porous carbons for oxidative degradation of emerging contaminants
Tian WJ, Zhang HY, Qian Z, Ouyang TH, Sun HQ, Qin JY, Tade MO, Wang SB
Applied Catalysis B: Environmental, 225, 76, 2018 |
| 5 |
First-principles investigation of CO adsorption on pristine, C-doped and N-vacancy defected hexagonal AlN nanosheets
Ouyang TH, Qian Z, Ahuja R, Liu XF
Applied Surface Science, 439, 196, 2018 |
| 6 |
Effect of defects on adsorption characteristics of AlN monolayer towards SO2 and NO2: Ab initio exposure
Ouyang TH, Qian Z, Hao XP, Ahuja R, Liu XF
Applied Surface Science, 462, 615, 2018 |
| 7 |
Predictive model of yaw error in a wind turbine
Ouyang TH, Kusiak A, He YS
Energy, 123, 119, 2017 |
| 8 |
A combined multivariate model for wind power prediction
Ouyang TH, Zha XM, Qin L
Energy Conversion and Management, 144, 361, 2017 |
| 9 |
Modeling wind-turbine power curve: A data partitioning and mining approach
Ouyang TH, Kusiak A, He YS
Renewable Energy, 102, 1, 2017 |
| 10 |
Model of selecting prediction window in ramps forecasting
Ouyang TH, Zha XM, Qin L, Xiong Y, Huang HM
Renewable Energy, 108, 98, 2017 |
