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个人简介

崔秋实,重庆大学电气工程学院副教授,重庆英才·青年拔尖人才,上海高校特聘教授(东方学者),李文沅院士团队青年骨干成员。担任IEEE电力与能源协会大数据分析委员会网络论坛任务组副主席,大数据辅导系列论坛创始主席。硕士和博士分别毕业于美国伊利诺伊理工大学(IIT)和加拿大麦吉尔大学(McGill),在加拿大欧泊实时仿真公司(OPAL-RT)和美国亚利桑那州立大学(ASU)担任过研发工程师和博士后研究员。他的研究紧密结合人工智能,大数据,电力系统和新能源并网,主要研究方向包括电力系统人工智能,医工结合,电力系统保护与控制,综合能源系统,新能源并网测试,电网实时仿真与数字孪生等。 现为李文沅院士团队核心成员,招收博士、硕士等,课题组(AI for Power Systems)拥有良好的科研平台和国际化背景,欢迎新同学加入! 崔博士是加拿大自然科学与工程技术研究(NSERC)博士后基金获得者,加拿大魁北克省自然科技基金(FRQNT)博士后基金获得者。2016-2019年,崔博士分别在英国、美国、中国举办的三个国际会议(第13届IET电力系统保护发展会议,第51届北美电力研讨会,和2019 IEEE可持续能源和电力会议)获得了最佳论文奖,排名均为第一。近五年主持加拿大自然科学基金项目等6项,领导并参与了十多个国家级和省级项目,包括美国自然科学基金,美国能源部,美国能源部先进研究计划署,美国电力系统工程研究中心,美国国家电力科学研究院,美国亚利桑那州盐河水力和电力供应项目,和加拿大魁北克省自然科技基金等。 崔博士拥有丰富的工业及工程经验,为OPAL-RT公司提出了人工智能技术应用于电网保护的通用框架,打通了人工智能算法与硬件在环测试之间的技术壁垒,通过Python API接口编程实现了多场景仿真的自动运行,开发了世界首个Hypersim微电网系统以及基于Matlab Simulink的继电保护模块库,公司该产品的销售额达到每年3000多万美元。崔博士领导的创业团队,开发了新能源电动车充电桩并网规划与运营云计算和分析工具,从全球几百个项目中脱颖而出,入选中国教育部举办的第13届“春晖杯”海外留学生创新创业大赛决赛能源组前六名,获得第三届南通创业创新大赛技术创新奖。

研究领域

电网人工智能技术 电网大数据 新型电力系统保护和控制 电力系统人工智能 医工结合 电力系统保护与控制 综合能源系统 新能源并网测试 电网实时仿真与数字孪生

近期论文

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预印 [1] Y. Tan, B. Jin, Q. Cui, X. Yue, and A. Sangiovanni-Vincentelli, “Generalizing Fault Detection Against Domain Shifts Using Stratification-Aware Cross-Validation,” arXiv preprint arXiv:2008.08713, 2020. (Collaboration with the Co-founder of Electronic Design Automation (EDA) software) 期刊出版物 [2] X. Tang, Q. Cui*, Y. Weng, Y. Su and D. Li, “Identify Incipient Faults Through Similarity Comparison with Waveform Split-Recognition Framework”, Frontier in Energy Research, Feb. 2023. [3] Y. Wang, Q. Cui*, Y. Weng, D. Li and W. Li, “Learning Picturized and Time-series Data for Fault Location with Renewable Energy Sources”, International Journal of Electrical Power and Energy Systems, Nov. 2022. [4] H. Wang, Y. Ye, Y. Chen, Y. Chen, Q. Yang, Q. Cui, and P. You, “AI, Data Analytics, and Mechanism Design for DER Integration Toward Net Zero”. Frontiers in Energy Research, p.1836, 2022. [5] Y. Weng, S. Luo, Q. Cui*, R. Trask, and H. Wang, “House-Level Storage Device,” IEEE Transactions on Smart Grid, vol. 14, no. 1, pp. 464 - 475, Jan. 2023. [6] Y. Weng, Q. Cui*, and M. Guo, “Transform Waveforms into Signature Vectors for General-purpose Incipient Fault Detection,” IEEE Transactions on Power Delivery, vol. 37, no. 6, pp. 4559 - 4569, Dec. 2022. [7] Q. Cui, G. Kim, and Y. Weng, “Twin-Delayed Deep Deterministic Policy Gradient for Low Frequency Oscillation Damping Control,” Energies, 14(20): 6695, 2021. [8] T. Chen, C. Gao, H. Hui, Q. Cui, H. Long, “A generalized additive model-based data-driven solution for lithium-ion battery capacity prediction and local effects analysis,” Transactions of the Institute of Measurement and Control, Nov. 2021. [9] S. Phommixay, M.L. Doumbia and Q. Cui, “Comparative analysis of continuous and hybrid binary-continuous particle swarm optimization for optimal economic operation of a microgrid,” Process Integration and Optimization for Sustainability (2021). [10] S. Phommixay, M.L. Doumbia and Q. Cui, “A Two-layer Optimization Approach for Economic Operation of a Microgrid Under a Planned Outage,” Sustainable Cities and Society, Volume 66, Mar. 2021. [11] T. Chen, Q. Cui, C. Gao, Q. Hu, K. Lai, J. Yang, R. Lyu, H. Zhang, and J. Zhang, “Optimal demand response strategy of commercial Building-based virtual power plant using reinforcement learning,” IET Generation, Transmission & Distribution, Vol. 15, Issue 16, pp. 2309-2318, Aug. 2021. [12] Q. Cui, and Y. Weng, “An Environment-adaptive Protection Scheme with Long-term Reward for Distribution Networks,” International Journal of Electrical Power and Energy Systems, 124, p.106350. [13] Q. Cui, S. M. Yousaf, Y. Weng, and M. Dyer, “Reinforcement Learning Based Recloser Control for Distribution Cables with Degraded Insulation Level,” IEEE Transactions on Power Delivery, vol. 36, no. 2, pp. 1118-1127, April 2021. [14] Q. Cui, and Y. Weng, “Enhance High Impedance Fault Detection and Location Accuracy via μ-PMUs,” IEEE Transactions on Smart Grid, vol. 11, no. 1, pp. 797-809, Jan. 2020. [15] Q. Cui, Y. Weng, and C. W. Tan, “Electric Vehicle Charging Station Placement Method for Urban Areas,” IEEE Transactions on Smart Grid, vol. 10, no. 6, pp. 6552-6565, Nov. 2019. [16] Q. Cui, K. El-Arroudi, and Y. Weng, “A Feature Selection Method for High Impedance Fault Detection,” IEEE Transactions on Power Delivery, vol. 34, no. 3, pp. 1203-1215, Jun. 2019. [17] Q. Cui, K. El-Arroudi, and G. Joos, “Islanding Detection of Hybrid Distributed Generation Under Reduced Non-Detection Zone,” IEEE Transactions on Smart Grid, vol. 9, no. 5, pp. 5027-5037, Sep. 2018. [18] Q. Cui, K. El-Arroudi, and G. Joos, “Real-time Hardware-in-the-loop Simulation for Islanding Detection Schemes in Hybrid Distributed Generation Systems,” IET Generation, Transmission & Distribution, vol. 11, no. 12, pp. 3050-3056, Aug. 2017. 会议出版物 [19] Q. Cui, M. Guo and Y. Weng, “Sig2Vec: Dictionary Design for Incipient Faults in Distribution Systems,” IEEE Power and Energy Society General Meeting (PESGM), Orlando, FL, USA, 2023. [20] Q. Cui and Y. Weng, “Mining Partially Labeled Data from Edge Devices to Detect and Locate High Impedance Faults,” IEEE Sustainable Power & Energy Conference (iSPEC), Beijing, China, 2019 (最佳论文奖,200多篇论文中排名第一). [21] J. Yuan, Q. Cui, Z. Ma, and Y. Weng, “Learning EV Placement Factors with Social Welfare and Economic Variation Modeling,” North American Power Symposium (NAPS), Wichita, KS, USA, 2019 (最佳论文展示奖,203篇论文中排名第一) [22] Q. Cui, S. Li, K. El-Arroudi, and G. Joos, “Multifunction Intelligent Relay for Inverter-based Distributed Generation,” in Developments in Power System Protection (DPSP), 13th IET International Conference, Edinburgh, UK 2016 (最佳论文奖,200多篇论文中排名第一) 专利 [23] Q. Cui, Y. Weng, K. El-Arroudi, and S. Hashmy, “Effective Feature Set- Based High Impedance Fault Detector,” Provisional Patent Application No. 62/859,929 (Jun. 11, 2019). [24] Q. Cui, Y. Weng, “Enhance High Impedance Fault Detection and Location Accuracy via μ-PMUs,” Provisional Patent Application No. 63/039,215 (Jun. 15, 2020). [25] Q. Cui, Y. Weng, “Reinforcement Learning Based Recloser Control for Distribution Cables with Degraded Insulation Level,” Provisional Patent Application No. 63/105,629 (Oct. 26, 2020).

学术兼职

IEEE PES 大数据分析委员会 网络论坛工作组副主席(2019年11月-至今) 大数据辅导系列论坛创始主席创办主席(2019年3月-至今) 网络论坛任务组副主席(2018年1月-2019年11月) 演讲嘉宾,“世界能源脱碳路径”,全球绿色发展联盟(Global Green Development Alliance),“健康世界-绿色发展”系列讲座第73期(2023年2月) 客座编辑,Frontiers In Smart Grids: Next-generation Smart Grid with AI and Advanced Energy Infrastructure towards Low Carbon Future and Net-zero(2022年10月) 执行主席,电力行业储能技术与应用研讨 2022年会(2022年9月) 技术委员会主席 (TPC), IEEE SmartGridComm’22(2022年8月) 分论坛主席,5th International Electrical and Energy Conference(CIEEC 2022),分论坛名称: New Energy Power System(2022年5月) 分论坛主席,5th International Conference on Energy, Electrical and Power Engineering(CEEPE 2022),分论坛名称: AI Green Energy(2022年4月) 主讲嘉宾,大会组织委员会主席,第二届工业技术与智能管理国际学术会议(ICITIM 2022)(2022年1月) 分论坛主席,IEEE Sustainable Power and Energy Conference(iSPEC 2021),分论坛名称: Fault Diagnosis and Detection(2021年12月) 分论坛主席,11th International Conference on Power and Energy Systems(ICPES 2021),分论坛名称: New energy based modern power system(2021年12月) 客座编辑,Frontiers in Energy Research: AI, Data Analytics, and Mechanism Design for DER Integration Toward Net Zero(2021年11月) 专题论坛主席,第52届北美电力研讨会,分论坛名称: 电力系统应用中的人工智能和机器学习(2021年4月) IEEE菲尼克斯地区会议执行主席(2020年1月至2021年4月) IEEE北美电力研讨会核心成员(2020年7月) 国际知名期刊及会议审稿人(2016年-至今) 期刊:IEEE Transactions on {Smart Grid, Power Delivery, Power Systems, Industrial Informatics, Intelligent Transportation Systems, Transportation Electrification, Vehicular Technology}, IET Generation, Transmission and Distribution, Renewable Power Generation, Smart Grid, Science, Measurement and Technology, IEEE PES Letters, IEEE Systems Journal, International Journal of Electrical Power & Energy Systems, Journal of Modern Power Systems & Clean Energy, Protection and Control of Modern Power Systems 会议:IEEE SmartGridComm’22, NAPS 2017 北美电力研讨会,CCECE 2018 电气与计机工程加拿大会议,iSPEC 2019电气与电子工程师学会可持续电力与能源会议 会员:电气与电子工程师学会: 电力与能源学会(2010年-至今)

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