学位: 博士研究生
邮箱:dafeng.zhu@sjtu.edu.cn
指导教师:杨博
年级:2018
学位: 博士研究生
邮箱:dafeng.zhu@sjtu.edu.cn
指导教师:杨博
年级:2018
2022.10-2023.10 南洋理工大学 电气工程 联培博士
2018.09-2023.09 上海交通大学 控制科学与工程 博士生
2023年 上海交通大学优秀博士毕业生发展奖学金
2023年 上海市自动化学会最佳论文奖
2022年 上海交通大学三好学生
2021年 国家留学基金委资助留学
2020年 国家奖学金
2020年 第四届“长风杯”全国大学生大数据分析与挖掘竞赛全国二等奖
2014年 中国矿业大学(北京)优秀毕业生、优秀毕业论文
2013年 中国矿业大学(北京)校级优秀学生特等奖学金
期刊论文
[1] D. Zhu, B. Yang, L. Li, Y. Wu, H. Deng, Z. Dong, K. Ma and X. Guan, “Industrial Production Decision Making and Energy Management with Optimization-Guided Learning,” IEEE Transactions on Smart Grid, accepted, 2025.
[2] D. Zhu, B. Yang, Y. Wu, H. Deng, Z. Dong, K. Ma and X. Guan, “Joint Trading and Scheduling among Coupled Carbon-Electricity-Heat-Gas Industrial Clusters,” IEEE Transactions on Smart Grid, vol. 15, no. 3, pp. 3152-3164, May 2024.
[3] D. Zhu, B. Yang, C. Ma, Z. Wang, S. Zhu, K. Ma and X. Guan, "Stochastic Gradient-based Fast Distributed Multi-Energy Management for an Industrial Park with Temporally-Coupled Constraints," Applied Energy, vol. 317: 119107, July 2022.
[4] D. Zhu, B. Yang, Y. Liu, Z. Wang, K. Ma and X. Guan, "Energy Management Based on Multi-Agent Deep Reinforcement Learning for A Multi-Energy Industrial Park," Applied Energy, vol. 311: 118636, Apr. 2022.
[5] D. Zhu, B. Yang, Q. Liu, K. Ma, S. Zhu, C. Ma and X. Guan, "Energy trading in microgrids for synergies among electricity, hydrogen and heat networks," Applied Energy, vol. 272: 115225, Aug. 2020.
[6] D. Zhu, H. Mao, W. Yin and L. Wang, “Design of high-precision temperature control system for inertial platform,” Mechanical Design and Research, vol. 34, no. 4, pp. 113-115, 2018. (In Chinese).
[7] D. Zhu, H. Mao, Q. Zhang and L. Wang, “An Algorithm for Extracting the Earth's Ultraviolet Center Based on Point Hough,” Optics and Optoelectronics Technology, vol. 15, no. 1, pp. 20-23, 2017. (In Chinese).
[8] Y. Wu, B. Yang, D. Zhu, C. Chen and X. Guan, "Synergy Between Resource-Efficient Data Transmission and Precision-Adaptive Fault Diagnosis for High-Frequency Signals," IEEE Transactions on Industrial Informatics, doi: 10.1109/TII.2025.3534403.
[9] H. Deng, B. Yang, M. Chow, D. Zhu, G. Yao, C. Chen, X. Guan and D. Srinivasan, “A Decision-dependent Hydrogen Supply Infrastructure Planning Approach Considering Causality Between Vehicles and Stations,” IEEE Transactions on Sustainable Energy, vol. 15, no. 3, pp. 1914-1932, July 2024.
[10] Y. Wu, B. Yang, D. Zhu, Q. Liu, C. Li, C. Chen and X. Guan, "To Transmit or Predict: an Efficient Industrial Data Transmission Scheme with Deep Learning and Cloud-Edge Collaboration," IEEE Transactions on Industrial informatics, vol. 19, no. 11, pp. 11322-11332, Nov. 2023.
[11] Q. Liu, B. Yang, Z. Wang, D. Zhu, X. Wang, K. Ma and X. Guan, "Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations," IEEE Transactions on Network Science and Engineering, vol. 9, no. 3, pp. 1680-1696, 1 May-June 2022.
会议论文
[1] D. Zhu, B. Yang, Z. Wang, C. Ma, K. Ma, and S. Zhu, "Fast Distributed Stochastic Scheduling for A Multi-Energy Industrial Park," 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS), 2021, pp. 885-890.
[2] D. Zhu, B. Yang, Q. Liu, K. Ma, S. Zhu and X. Guan, "Joint Energy Trading and Scheduling for Multi-Energy Microgrids with Storage," 2020 39th Chinese Control Conference (CCC), 2020, pp. 1617-1622.
[3] D. Zhu and Q. Xu, “Decarbonizing Steel Heating: Energy Scheduling Optimization with Battery Storage and Hydrogen,” 2025 IEEE Power & Energy Society General Meeting (PESGM), Austin, Texas, USA, accepted.
[4] D. Zhu and Q. Xu, “Energy Sharing among Hydrogen-based Regional Energy Systems with Multi-Energy Storage,” 2024 IEEE Energy Conversion Congress and Exposition (ECCE), Phoenix, AZ, USA, 2024, pp. 1157-1162.
[5] H. Deng, B. Yang, D. Zhu, G. Yao, X. Guan and D. Srinivasan, "Hydrogen Supply Infrastructure Planning Method Considering Indirect Network Effects," 2024 IEEE Energy Conversion Congress and Exposition (ECCE), Phoenix, AZ, USA, 2024, pp. 654-661,
[6] Y. Wu, B. Yang, D. Zhu and C. Chen, "LI-DPS: A Long Sequence Dual Prediction Scheme Based on Informer for Efficient High-Frequency Data Transmission," IECON 2024 - 50th Annual Conference of the IEEE Industrial Electronics Society, Chicago, IL, USA, 2024, pp. 1-6.
[7] S. He, B. Yang, D. Zhu and C. Li, "Surface Defect Detection Based on Deep Learning and Collaborative Cloud-edge Computation," 2021 7th International Conference on Computer and Communications (ICCC), 2021, pp. 1469-1474.
[8] Q. Liu, B. Yang, Z. Wang, X. Wang, D. Zhu and X. Guan, "A PV Fault Diagnosis Framework Based on Asynchronous Federated Learning," 2022 13th Asian Control Conference (ASCC), 2022, pp. 494-499.
[9] Y. Wu, B. Yang, C. Li, Q. Liu, Y. Liu and D. Zhu, "A Deep Learning Based Efficient Data Transmission for Industrial Cloud-Edge Collaboration," 2022 IEEE 31st International Symposium on Industrial Electronics (ISIE), 2022, pp. 1202-1207.