| Correlation-constrained and sparsity-controlled vector autoregressive model for spatio-temporal wind power forecasting Y Zhao, L Ye, P Pinson, Y Tang, P Lu IEEE Transactions on Power Systems 33 (5), 5029-5040, 2018 | 174 | 2018 |
| Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges P Lu, L Ye, Y Zhao, B Dai, M Pei, Y Tang Applied Energy 301, 117446, 2021 | 146 | 2021 |
| Hierarchical model predictive control strategy based on dynamic active power dispatch for wind power cluster integration L Ye, C Zhang, Y Tang, W Zhong, Y Zhao, P Lu, B Zhai, H Lan, Z Li IEEE Transactions on power systems 34 (6), 4617-4629, 2019 | 128 | 2019 |
| A novel spatio-temporal wind power forecasting framework based on multi-output support vector machine and optimization strategy P Lu, L Ye, W Zhong, Y Qu, B Zhai, Y Tang, Y Zhao Journal of Cleaner Production 254, 119993, 2020 | 73 | 2020 |
| A combined model for short-term wind power forecasting based on the analysis of numerical weather prediction data B He, L Ye, M Pei, P Lu, B Dai, Z Li, K Wang Energy Reports 8, 929-939, 2022 | 63 | 2022 |
| Short-term wind power forecasting based on meteorological feature extraction and optimization strategy P Lu, L Ye, M Pei, Y Zhao, B Dai, Z Li Renewable Energy 184, 642-661, 2022 | 63 | 2022 |
| A new hybrid prediction method of ultra-short-term wind power forecasting based on EEMD-PE and LSSVM optimized by the GSA P Lu, L Ye, B Sun, C Zhang, Y Zhao, J Teng Energies 11 (4), 697, 2018 | 62 | 2018 |
| A spatiotemporal directed graph convolution network for ultra-short-term wind power prediction Z Li, L Ye, Y Zhao, M Pei, P Lu, Y Li, B Dai IEEE Transactions on Sustainable Energy 14 (1), 39-54, 2022 | 60 | 2022 |
| An ensemble method for short-term wind power prediction considering error correction strategy L Ye, B Dai, Z Li, M Pei, Y Zhao, P Lu Applied Energy 322, 119475, 2022 | 57 | 2022 |
| Combined approach for short-term wind power forecasting based on wave division and Seq2Seq model using deep learning L Ye, B Dai, M Pei, P Lu, J Zhao, M Chen, B Wang IEEE Transactions on Industry Applications 58 (2), 2586-2596, 2022 | 52 | 2022 |
| Feature extraction of meteorological factors for wind power prediction based on variable weight combined method P Lu, L Ye, Y Zhao, B Dai, M Pei, Z Li Renewable Energy 179, 1925-1939, 2021 | 49 | 2021 |
| Ultra-short-term combined prediction approach based on kernel function switch mechanism P Lu, L Ye, Y Tang, Y Zhao, W Zhong, Y Qu, B Zhai Renewable Energy 164, 842-866, 2021 | 42 | 2021 |
| A novel integrated method for short-term wind power forecasting based on fluctuation clustering and history matching L Ye, Y Li, M Pei, Y Zhao, Z Li, P Lu Applied Energy 327, 120131, 2022 | 36 | 2022 |
| Study of assessment on capability of wind power accommodation in regional power grids L Ye, C Zhang, H Xue, J Li, P Lu, Y Zhao Renewable Energy 133, 647-662, 2019 | 36 | 2019 |
| 基于模型预测控制的风电集群多时间尺度有功功率优化调度策略研究 路朋， 叶林， 汤涌， 张慈杭， 仲悟之， 孙舶皓， 翟丙旭， 曲莹， 刘新元 中国电机工程学报 39 (22), 6572-6583, 2019 | 23 | 2019 |
| 含风电电力系统有功功率模型预测控制方法综述 叶林， 路朋， 赵永宁， 戴斌华， 汤涌 中国电机工程学报 41 (18), 6181-6198, 2021 | 21 | 2021 |
| 基于天气分型的短期光伏功率组合预测方法 叶林， 裴铭， 路朋， 赵金龙， 何博宇 电力系统自动化 45 (1), 44-54, 2021 | 21 | 2021 |
| Combined Gaussian mixture model and cumulants for probabilistic power flow calculation of integrated wind power network L Ye, Y Zhang, C Zhang, P Lu, Y Zhao, B He Computers & Electrical Engineering 74, 117-129, 2019 | 21 | 2019 |
| 基于混合储能双层规划模型的风电波动平抑策略 马兰， 谢丽蓉， 叶林， 路朋， 王凯丰 电网技术 46 (3), 1016-1026, 2022 | 17 | 2022 |
| Wind and photovoltaic power time series data aggregation method based on an ensemble clustering and Markov chain J Jin, L Ye, J Li, Y Zhao, P Lu, W Wang, X Wang CSEE Journal of Power and Energy Systems 8 (3), 757-768, 2021 | 17 | 2021 |