吴江华
职务/职称
深圳市大数据研究院信息系统大数据实验室研究科学家
研究方向
电力系统优化、混合整数规划、最优化算法以及机器学习
电子邮箱
wujianghua@sribd.cn
教育背景
2014.08 – 2018.08 沈阳建筑大学，建筑电气智能化，学士
2018.08 – 2023.08 康涅狄格大学，电气与计算机工程，博士
个人介绍
吴江华博士于2023年在美国康涅狄格大学（University of Connecticut）的电气与计算机工程（Electrical and Computer Engineering）学院取得博士学位，同年9月加入深圳市大数据研究院，担任研究科学家。他现在的主要研究兴趣是分布式能源的并网及电力系统优化、考虑新能源及储能的新型电网优化，最优化算法以及传统优化算法与机器学习的融合。
代表性论文
1. J. Wu, P. Luh, Y. Chen, M. Bragin and B. Yan, “A Novel Optimization Approach for Subhourly Unit Commitment with Large Numbers of Units and Virtual Transactions,” IEEE Transactions on Power Systems, vol. 37, no. 5, pp. 3716–3725, Sep. 2022.
2. J. Wu, P. Luh, Y. Chen, B. Yan and M. Bragin, “Synergistic Integration of Machine Learning and Mathematical Optimization for Unit Commitment,” IEEE Transactions on Power Systems, Jan. 2023. (Accepted)
3. J. Wu, Z. Wang, Y. Chen, B. Yan and M. A. Bragin, P. B. Luh, “A Hybrid Machine Learning and Optimization Approach with Feasibility Layer Assistance for Sub-hourly Unit Commitment,” (Under Review)
4. W. Lin, J. Hua, H. Jian, J. Xue, J. Wu, C. Wang and Z. Lin, “High-dimension tie-line security regions for renewable accommodations,” Energy, vol 270, May 2023, 126887.
5. J. Wu, P. B. Luh, Y. Chen, B. Yan, and M. A. Bragin, “A Decomposition and Coordination Approach for Large Sub-hourly Unit Commitment,” 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC, Aug. 2020.
