| Deep learning-based interval state estimation of AC smart grids against sparse cyber attacks H Wang, J Ruan, G Wang, B Zhou, Y Liu, X Fu, J Peng IEEE Transactions on Industrial Informatics 14 (11), 4766-4778, 2018 | 263 | 2018 |
| Statistical machine learning model for stochastic optimal planning of distribution networks considering a dynamic correlation and dimension reduction X Fu, Q Guo, H Sun IEEE Transactions on Smart Grid 11 (4), 2904-2917, 2020 | 133 | 2020 |
| Statistical machine learning model for capacitor planning considering uncertainties in photovoltaic power X Fu Protection and Control of Modern Power Systems 7 (1), 1-13, 2022 | 131 | 2022 |
| Collaborative optimization of PV greenhouses and clean energy systems in rural areas X Fu, Y Zhou IEEE Transactions on Sustainable Energy 14 (1), 642-656, 2022 | 123 | 2022 |
| Optimal allocation and adaptive VAR control of PV-DG in distribution networks X Fu, H Chen, R Cai, P Yang Applied Energy 137, 173-182, 2015 | 90 | 2015 |
| Key technologies and applications of agricultural energy internet for agricultural planting and fisheries industry X Fu, H Niu Information Processing in Agriculture 10 (3), 416-437, 2023 | 79 | 2023 |
| Uncertainty analysis of an integrated energy system based on information theory X Fu, H Sun, Q Guo, Z Pan, W Xiong, L Wang Energy 122, 649-662, 2017 | 78 | 2017 |
| Deep learning aided interval state prediction for improving cyber security in energy internet H Wang, J Ruan, Z Ma, B Zhou, X Fu, G Cao Energy 174, 1292-1304, 2019 | 76 | 2019 |
| Planning of distributed renewable energy systems under uncertainty based on statistical machine learning X Fu, X Wu, C Zhang, S Fan, N Liu Protection and Control of Modern Power Systems 7 (4), 1-27, 2022 | 71 | 2022 |
| Probabilistic power flow analysis considering the dependence between power and heat X Fu, H Sun, Q Guo, Z Pan, X Zhang, S Zeng Applied energy 191, 582-592, 2017 | 57 | 2017 |
| Power quality comprehensive evaluation method for distributed generation X Fu, H Chen, G Liu, XM Jin Proceedings of the CSEE 34 (25), 4270-4276, 2014 | 52 | 2014 |
| Estimation of the failure probability of an integrated energy system based on the first order reliability method X Fu, Q Guo, H Sun, X Zhang, L Wang Energy 134, 1068-1078, 2017 | 50 | 2017 |
| Failure probability estimation of the gas supply using a data-driven model in an integrated energy system X Fu, G Li, X Zhang, Z Qiao Applied Energy 232, 704-714, 2018 | 49 | 2018 |
| Failure probability estimation of gas supply using the central moment method in an integrated energy system X Fu, X Zhang Applied Energy 219, 1-10, 2018 | 45 | 2018 |
| A review on basic theory and technology of agricultural energy internet X Zhang, X Fu, Y Xue, X Chang, X Bai IET Renewable Power Generation 18 (7), 1318-1331, 2024 | 43 | 2024 |
| Crop pest image recognition based on the improved ViT method X Fu, Q Ma, FF Yang, C Zhang, X Zhao, F Chang, L Han Information Processing in Agriculture 11 (2), 249-259, 2024 | 40 | 2024 |
| A review of key technologies and trends in the development of integrated heating and power systems in agriculture X Fu, Y Zhou, F Yang, L Ma, H Long, Y Zhong, P Ni Entropy 23 (2), 260, 2021 | 40 | 2021 |
| Typical scenario set generation algorithm for an integrated energy system based on the Wasserstein distance metric X Fu, Q Guo, H Sun, Z Pan, W Xiong, L Wang Energy 135, 153-170, 2017 | 36 | 2017 |
| Key technologies and applications of rural energy internet in China H Long, X Fu, W Kong, H Chen, Y Zhou, F Yang Information Processing in Agriculture, 2022 | 35 | 2022 |
| Unscented Kalman Filter based interval state estimation of cyber physical energy system for detection of dynamic attack H Wang, A Meng, Y Liu, X Fu, G Cao Energy 188, 116036, 2019 | 33 | 2019 |