| Overview of wind power intermittency: Impacts, measurements, and mitigation solutions G Ren, J Liu, J Wan, Y Guo, D Yu Applied Energy 204, 47-65, 2017 | 295 | 2017 |
| Spatial and temporal assessments of complementarity for renewable energy resources in China G Ren, J Wan, J Liu, D Yu Energy 177, 262-275, 2019 | 118 | 2019 |
| Analysis of wind power intermittency based on historical wind power data G Ren, J Wan, J Liu, D Yu, L Söder Energy 150, 482-492, 2018 | 76 | 2018 |
| Multi-step wind speed prediction based on turbulence intensity and hybrid deep neural networks F Li, G Ren, J Lee Energy conversion and management 186, 306-322, 2019 | 73 | 2019 |
| The analysis of turbulence intensity based on wind speed data in onshore wind farms G Ren, J Liu, J Wan, F Li, Y Guo, D Yu Renewable energy 123, 756-766, 2018 | 68 | 2018 |
| Characterization of wind resource in China from a new perspective G Ren, J Wan, J Liu, D Yu Energy 167, 994-1010, 2019 | 53 | 2019 |
| Day-ahead prediction of wind speed with deep feature learning J Wan, J Liu, G Ren, Y Guo, D Yu, Q Hu International Journal of Pattern Recognition and Artificial Intelligence 30 …, 2016 | 50 | 2016 |
| Variogram time-series analysis of wind speed J Liu, G Ren, J Wan, Y Guo, D Yu Renewable energy 99, 483-491, 2016 | 32 | 2016 |
| Measurement and statistical analysis of wind speed intermittency G Ren, J Liu, J Wan, Y Guo, D Yu, J Liu Energy 118, 632-643, 2017 | 31 | 2017 |
| Spatial and temporal correlation analysis of wind power between different provinces in China G Ren, J Wan, J Liu, D Yu Energy 191, 116514, 2020 | 27 | 2020 |
| A novel metric for assessing wind and solar power complementarity based on three different fluctuation states and corresponding fluctuation amplitudes G Ren, W Wang, J Wan, F Hong, K Yang Energy Conversion and Management 278, 116721, 2023 | 20 | 2023 |
| Assessing temporal variability of wind resources in China and the spatial correlation of wind power in the selected regions G Ren, J Wan, J Liu, D Yu Journal of renewable and sustainable energy 12 (1), 2020 | 19 | 2020 |
| Ultra-short-term wind speed prediction based on multi-scale predictability analysis J Wan, G Ren, J Liu, Q Hu, D Yu Cluster Computing 19, 741-755, 2016 | 15 | 2016 |
| Investigating the complementarity characteristics of wind and solar power for load matching based on the typical load demand in China G Ren, J Liu, J Wan, W Wang, F Fang, F Hong, D Yu IEEE Transactions on Sustainable Energy 13 (2), 778-790, 2021 | 14 | 2021 |
| Quantitative insights into the differences of variability and intermittency between wind and solar resources on spatial and temporal scales in China G Ren, J Wan, W Wang, J Liu, F Hong, D Yu Journal of Renewable and Sustainable Energy 13 (4), 2021 | 9 | 2021 |
| Prediction of the standard deviation of wind speed turbulence GR Ren, JF Liu, J Wan, YF Guo, QH Hu, DR Yu Journal of Environmental Informatics 32 (1), 1-13, 2018 | 7 | 2018 |
| Investigating the impacts of spatial-temporal variation features of air density on assessing wind power generation and its fluctuation in China GR Ren, W Wang, J Wan, F Hong, K Yang, DR Yu Science China Technological Sciences 66 (6), 1797-1814, 2023 | 6 | 2023 |
| A universal power-law model for wind speed uncertainty J Wan, J Liu, G Ren, Y Guo, W Hao, J Yu, D Yu Cluster Computing 22, 10347-10359, 2019 | 4 | 2019 |
| Multi-scale DBNs regression model and its application in wind speed forecasting X Zhao, J Wan, G Ren, J Liu, J Chang, D Yu 2016 IEEE Advanced Information Management, Communicates, Electronic and …, 2016 | 4 | 2016 |
| A direct prediction method for wind power ramp events considering the class imbalanced problem G Ren, J Wan, Y Wang, K Yao, J Fu, J Yu Energy Science & Engineering 11 (5), 1705-1715, 2023 | 1 | 2023 |
