| A systematic review of enhanced (or engineered) geothermal systems: past, present and future K Breede, K Dzebisashvili, X Liu, G Falcone Geothermal Energy 1, 1-27, 2013 | 483 | 2013 |
| 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 | 256 | 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 | 237 | 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 | 219 | 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 | 168 | 2020 |
| A systematic study of harnessing low-temperature geothermal energy from oil and gas reservoirs X Liu, G Falcone, C Alimonti Energy 142, 346-355, 2018 | 136 | 2018 |
| 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 | 123 | 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 | 121 | 2022 |
| Assessment of deep geothermal energy exploitation methods: The need for novel single-well solutions G Falcone, X Liu, RR Okech, F Seyidov, C Teodoriu Energy 160, 54-63, 2018 | 121 | 2018 |
| 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 | 89 | 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 | 81 | 2021 |
| Anomaly detection in wind turbine SCADA data for power curve cleaning R Morrison, X Liu, Z Lin Renewable Energy 184, 473-486, 2022 | 55 | 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 | 44 | 2021 |
| 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 | 24 | 2022 |
| Impacts of water depth increase on offshore floating wind turbine dynamics Z Lin, X Liu, S Lotfian Ocean Engineering 224, 108697, 2021 | 22 | 2021 |
| Review of variable speed drive technology in beam pumping units for energy-saving C Tan, ZM Feng, X Liu, J Fan, W Cui, R Sun, Q Ma Energy Reports 6, 2676-2688, 2020 | 22 | 2020 |
| 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 | 22 | 2020 |
| A comprehensive assessment of correlations for two-phase flow through Venturi tubes X Liu, L Lao, G Falcone Journal of Natural Gas Science and Engineering 78, 103323, 2020 | 19 | 2020 |
| Convenient Synthesis of Fluorescent Chromeno [4, 3-d] pyrimidines from Electron-Deficient 3-Vinylchromones NM Chernov, RV Shutov, AE Potapova, IP Yakovlev Synthesis 52 (01), 40-50, 2020 | 18 | 2020 |
| Selection method modelling and matching rule for rated power of prime motor used by beam pumping units ZM Feng, J Tan, X Liu, X Fang Journal of Petroleum Science and Engineering 153, 197-202, 2017 | 16 | 2017 |
