| Short-term load forecasting with deep residual networks K Chen, K Chen, Q Wang, Z He, J Hu, J He IEEE Transactions on Smart Grid 10 (4), 3943-3952, 2018 | 602 | 2018 |
| Fault detection, classification and location for transmission lines and distribution systems: a review on the methods K Chen, C Huang, J He High voltage 1 (1), 25-33, 2016 | 376 | 2016 |
| Detection and classification of transmission line faults based on unsupervised feature learning and convolutional sparse autoencoder K Chen, J Hu, J He IEEE Transactions on Smart Grid 9 (3), 1748-1758, 2016 | 239 | 2016 |
| Fault location in power distribution systems via deep graph convolutional networks K Chen, J Hu, Y Zhang, Z Yu, J He IEEE Journal on Selected Areas in Communications 38 (1), 119-131, 2019 | 237 | 2019 |
| Scale-and context-aware convolutional non-intrusive load monitoring K Chen, Y Zhang, Q Wang, J Hu, H Fan, J He IEEE Transactions on Power Systems 35 (3), 2362-2373, 2019 | 119 | 2019 |
| Convolutional sequence to sequence non‐intrusive load monitoring K Chen, Q Wang, Z He, K Chen, J Hu, J He the Journal of Engineering 2018 (17), 1860-1864, 2018 | 101 | 2018 |
| A framework for automatically extracting overvoltage features based on sparse autoencoder K Chen, J Hu, J He IEEE Transactions on Smart Grid 9 (2), 594-604, 2016 | 100 | 2016 |
| Probabilistic short-term wind power forecasting based on deep neural networks W Wu, K Chen, Y Qiao, Z Lu 2016 international conference on probabilistic methods applied to power …, 2016 | 82 | 2016 |
| Identification of partial discharge defects based on deep learning method L Duan, J Hu, G Zhao, K Chen, J He, SX Wang IEEE Transactions on Power Delivery 34 (4), 1557-1568, 2019 | 72 | 2019 |
| A novel data-driven approach for residential electricity consumption prediction based on ensemble learning K Chen, J Jiang, F Zheng, K Chen Energy 150, 49-60, 2018 | 61 | 2018 |
| Learning-based data analytics: Moving towards transparent power grids K Chen, Z He, SX Wang, J Hu, L Li, J He CSEE Journal of Power and Energy Systems 4 (1), 67-82, 2018 | 47 | 2018 |
| Method of inter‐turn fault detection for next‐generation smart transformers based on deep learning algorithm L Duan, J Hu, G Zhao, K Chen, SX Wang, J He High Voltage 4 (4), 282-291, 2019 | 42 | 2019 |
| M2gsnet: Multi-modal multi-task graph spatiotemporal network for ultra-short-term wind farm cluster power prediction H Fan, X Zhang, S Mei, K Chen, X Chen Applied Sciences 10 (21), 7915, 2020 | 34 | 2020 |
| Solar energy forecasting with numerical weather predictions on a grid and convolutional networks K Chen, Z He, K Chen, J Hu, J He 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), 1-5, 2017 | 26 | 2017 |
| Practical failure recognition model of lithium-ion batteries based on partial charging process K Chen, F Zheng, J Jiang, W Zhang, Y Jiang, K Chen Energy 138, 1199-1208, 2017 | 25 | 2017 |
| Fault detection for covered conductors with high-frequency voltage signals: From local patterns to global features K Chen, T Vantuch, Y Zhang, J Hu, J He IEEE Transactions on Smart Grid 12 (2), 1602-1614, 2020 | 16 | 2020 |
| An inversion method for evaluating lightning current waveform based on time series neural network G Yang, K Chen, Z Yu, Y Zhang, F Zhou, J He IEEE Transactions on Electromagnetic Compatibility 59 (3), 887-893, 2016 | 15 | 2016 |
| GP-NAS-ensemble: a model for the NAS Performance Prediction K Chen, L Yang, Y Chen, K Chen, Y Xu, L Li | 14 | 2022 |
| An explainable and robust method for fault classification and location on transmission lines J Fang, K Chen, C Liu, J He IEEE Transactions on Industrial Informatics 19 (10), 10182-10191, 2023 | 10 | 2023 |
| Data-driven residential customer aggregation based on seasonal behavioral patterns K Chen, J Hu, Z He 2017 IEEE Power & Energy Society General Meeting, 1-5, 2017 | 7 | 2017 |
Jinliang HEProfessor of Electrical Engineering, Tsinghua University在 tsinghua.edu.cn 的电子邮件经过验证
