| A critical review of wind power forecasting methods—past, present and future S Hanifi, X Liu, Z Lin, S Lotfian Energies 13 (15), 3764, 2020 | 360 | 2020 |
| Short-term offshore wind speed forecast by seasonal ARIMA-A comparison against GRU and LSTM X Liu, Z Lin, Z Feng Energy 227, 120492, 2021 | 352 | 2021 |
| Wind power forecasting–A data-driven method along with gated recurrent neural network A Kisvari, Z Lin, X Liu Renewable Energy 163, 1895-1909, 2021 | 318 | 2021 |
| Wind power forecasting of an offshore wind turbine based on high-frequency SCADA data and deep learning neural network Z Lin, X Liu Energy 201, 117693, 2020 | 229 | 2020 |
| Short-term offshore wind power forecasting-A hybrid model based on Discrete Wavelet Transform (DWT), Seasonal Autoregressive Integrated Moving Average (SARIMA), and deep … W Zhang, Z Lin, X Liu Renewable Energy 185, 611-628, 2022 | 189 | 2022 |
| Wind power prediction based on high-frequency SCADA data along with isolation forest and deep learning neural networks Z Lin, X Liu, M Collu International Journal of Electrical Power & Energy Systems 118, 105835, 2020 | 146 | 2020 |
| Prediction of two-phase flow patterns in upward inclined pipes via deep learning Z Lin, X Liu, L Lao, H Liu Energy 210, 118541, 2020 | 117 | 2020 |
| Fault detection by an ensemble framework of Extreme Gradient Boosting (XGBoost) in the operation of offshore wind turbines P Trizoglou, X Liu, Z Lin Renewable Energy 179, 945-962, 2021 | 114 | 2021 |
| Anomaly detection in wind turbine SCADA data for power curve cleaning R Morrison, X Liu, Z Lin Renewable Energy 184, 473-486, 2022 | 85 | 2022 |
| Impact of Covid-19 pandemic on electricity demand in the UK based on multivariate time series forecasting with Bidirectional Long Short Term Memory X Liu, Z Lin Energy 227, 120455, 2021 | 61 | 2021 |
| A methodology to develop reduced-order models to support the operation and maintenance of offshore wind turbines Z Lin, D Cevasco, M Collu Applied Energy 259, 114228, 2020 | 45 | 2020 |
| Ensemble offshore wind turbine power curve modelling–an integration of isolation forest, fast radial basis function neural network, and metaheuristic algorithm T Li, X Liu, Z Lin, R Morrison Energy 239, 122340, 2022 | 39 | 2022 |
| Assessment of wind turbine aero-hydro-servo-elastic modelling on the effects of mooring line tension via deep learning Z Lin, X Liu Energies 13 (9), 2264, 2020 | 31 | 2020 |
| Impacts of water depth increase on offshore floating wind turbine dynamics Z Lin, X Liu, S Lotfian Ocean Engineering 224, 108697, 2021 | 28 | 2021 |
| Technology drivers in windfarm asset management M Barnes, K Brown, J Carmona, D Cevasco, M Collu, C Crabtree, ... Home Offshore, 2018 | 24 | 2018 |
| O&M cost-Based FMECA: Identification and ranking of the most critical components for 2-4 MW geared offshore wind turbines D Cevasco, M Collu, Z Lin Journal of Physics: Conference Series 1102 (1), 012039, 2018 | 20 | 2018 |
| An enhanced stiffness model for elastic lines and its application to the analysis of a moored floating offshore wind turbine Z Lin, P Sayer Ocean Engineering 109, 444-453, 2015 | 13 | 2015 |
| Investigation on PTO control of a Combined Axisymmetric Buoy-WEC (CAB-WEC) F Kong, W Su, H Liu, M Collu, Z Lin, H Chen, X Zheng Ocean Engineering 188, 106245, 2019 | 11 | 2019 |
| A Critical Review of Wind Power Forecasting Methods—Past, Present and Future. Energies 2020, 13, 3764 S Hanifi, X Liu, Z Lin, S Lotfian | 11 | |
| Lagrangian actuator model for wind turbine wake aerodynamics W Liu, J Shi, H Chen, H Liu, Z Lin, L Wang Energy 232, 121074, 2021 | 9 | 2021 |
