| 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 | 330 | 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 | 142 | 2019 |
| SolarNet: A sky image-based deep convolutional neural network for intra-hour solar forecasting C Feng, J Zhang Solar Energy 204, 71-78, 2020 | 141 | 2020 |
| 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 | 124 | 2018 |
| Probabilistic solar power forecasting based on weather scenario generation M Sun, C Feng, J Zhang Applied Energy 266, 114823, 2020 | 105 | 2020 |
| Conditional aggregated probabilistic wind power forecasting based on spatio-temporal correlation M Sun, C Feng, J Zhang Applied Energy 256, 113842, 2019 | 104 | 2019 |
| 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 | 103 | 2022 |
| 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 | 100 | 2017 |
| 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 | 98 | 2020 |
| 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 | 69 | 2021 |
| 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 | 68 | 2017 |
| A review of behind-the-meter solar forecasting BC Erdener, C Feng, K Doubleday, A Florita, BM Hodge Renewable and Sustainable Energy Reviews 160, 112224, 2022 | 65 | 2022 |
| Multi-distribution ensemble probabilistic wind power forecasting M Sun, C Feng, J Zhang Renewable Energy 148, 135-149, 2020 | 63 | 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 | 55 | 2019 |
| 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 | 48 | 2019 |
| Advances in solar forecasting: Computer vision with deep learning Q Paletta, G Terrén-Serrano, Y Nie, B Li, J Bieker, W Zhang, L Dubus, ... Advances in Applied Energy 11, 100150, 2023 | 45 | 2023 |
| 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 | 44 | 2019 |
| A learning-augmented approach for AC optimal power flow J Rahman, C Feng, J Zhang International Journal of Electrical Power & Energy Systems 130, 106908, 2021 | 40 | 2021 |
| 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 | 37 | 2018 |
| Machine learning-aided security constrained optimal power flow J Rahman, C Feng, J Zhang 2020 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2020 | 32 | 2020 |
Jie ZhangAssociate Professor, University of Texas at DallasPatvirtintas el. paštas utdallas.edu