| A data-driven multi-model methodology with deep feature selection for short-term wind forecasting C Feng, M Cui, BM Hodge, J Zhang Applied Energy 190, 1245-1257, 2017 | 283 | 2017 |
| Reinforced Deterministic and Probabilistic Load Forecasting via -Learning Dynamic Model Selection C Feng, M Sun, J Zhang IEEE Transactions on Smart Grid 11 (2), 1377-1386, 2019 | 101 | 2019 |
| Unsupervised clustering-based short-term solar forecasting C Feng, M Cui, BM Hodge, S Lu, HF Hamann, J Zhang IEEE Transactions on Sustainable Energy 10 (4), 2174-2185, 2018 | 87 | 2018 |
| Conditional aggregated probabilistic wind power forecasting based on spatio-temporal correlation M Sun, C Feng, J Zhang Applied Energy 256, 113842, 2019 | 77 | 2019 |
| Characterizing and analyzing ramping events in wind power, solar power, load, and netload M Cui, J Zhang, C Feng, AR Florita, Y Sun, BM Hodge Renewable energy 111, 227-244, 2017 | 76 | 2017 |
| Probabilistic solar power forecasting based on weather scenario generation M Sun, C Feng, J Zhang Applied Energy 266, 114823, 2020 | 64 | 2020 |
| SolarNet: A sky image-based deep convolutional neural network for intra-hour solar forecasting C Feng, J Zhang Solar Energy 204, 71-78, 2020 | 61 | 2020 |
| Deep learning-based real-time building occupancy detection using AMI data C Feng, A Mehmani, J Zhang IEEE Transactions on Smart Grid 11 (5), 4490-4501, 2020 | 61 | 2020 |
| Statistical representation of wind power ramps using a generalized Gaussian mixture model M Cui, C Feng, Z Wang, J Zhang IEEE Transactions on Sustainable Energy 9 (1), 261-272, 2017 | 54 | 2017 |
| Multi-distribution ensemble probabilistic wind power forecasting M Sun, C Feng, J Zhang Renewable Energy 148, 135-149, 2020 | 47 | 2020 |
| A two-step short-term probabilistic wind forecasting methodology based on predictive distribution optimization M Sun, C Feng, EK Chartan, BM Hodge, J Zhang Applied energy 238, 1497-1505, 2019 | 36 | 2019 |
| Reinforcement learning based dynamic model selection for short-term load forecasting C Feng, J Zhang 2019 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2019 | 34 | 2019 |
| A taxonomical review on recent artificial intelligence applications to PV integration into power grids C Feng, Y Liu, J Zhang International Journal of Electrical Power & Energy Systems 132, 107176, 2021 | 33 | 2021 |
| OpenSolar: Promoting the openness and accessibility of diverse public solar datasets C Feng, D Yang, BM Hodge, J Zhang Solar Energy 188, 1369-1379, 2019 | 32 | 2019 |
| Hourly-similarity based solar forecasting using multi-model machine learning blending C Feng, J Zhang 2018 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2018 | 30 | 2018 |
| Short-term global horizontal irradiance forecasting based on sky imaging and pattern recognition C Feng, M Cui, M Lee, J Zhang, BM Hodge, S Lu, HF Hamann 2017 IEEE Power & Energy Society General Meeting, 1-5, 2017 | 25 | 2017 |
| Convolutional neural networks for intra-hour solar forecasting based on sky image sequences C Feng, J Zhang, W Zhang, BM Hodge Applied Energy 310, 118438, 2022 | 24 | 2022 |
| Probabilistic wind power ramp forecasting based on a scenario generation method M Cui, C Feng, Z Wang, J Zhang, Q Wang, A Florita, V Krishnan, ... 2017 IEEE Power & Energy Society General Meeting, 1-1, 2017 | 24 | 2017 |
| Characterizing forecastability of wind sites in the United States C Feng, M Sun, M Cui, EK Chartan, BM Hodge, J Zhang Renewable Energy 133, 1352-1365, 2019 | 23 | 2019 |
| Assessment of aggregation strategies for machine-learning based short-term load forecasting C Feng, J Zhang Electric Power Systems Research 184, 106304, 2020 | 21 | 2020 |
Jie ZhangAssociate Professor, University of Texas at DallasVerificeret mail på utdallas.edu
