师资队伍
崔秋实
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崔秋实

学历:博士

职称:副教授

邮箱:qiushi.cui@qq.com

研究方向:电网人工智能技术,电网大数据,新型电力系统保护和控制,综合能源系统,人工智能在医工结合领域应用

 

个人简介

崔秋实, 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于20122017年分别毕业于美国伊利诺伊理工大学(IIT)和拿大麦吉尔大学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,电力系统保护与控制,综合能源系统,电动车并网,电网实时仿真与建模等。

崔秋实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“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。

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!

部分代表性工作:

期刊论文:

[1] Y. Weng, Q. Cui*, and M. Guo, “Transform Waveforms into Signature Vectors for General-purpose Incipient Fault Detection,” IEEE Transactions on Power Delivery, doi: 10.1109/TPWRD.2022.3151110.

[2] Q. Cui, G. Kim, and Y. Weng, “Twin-Delayed Deep Deterministic Policy Gradient for Low Frequency Oscillation Damping Control,” Energies, 14(20): 6695, 2021.

[3] 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.

[4] 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).

[5] A. Arif, K. Imran, Q. Cui and Y. Weng, “Islanding Detection for Inverter-Based Distributed Generation Using Unsupervised Anomaly Detection,” IEEE Access, 2021, 9: 90947-90963.

[6] 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.

[7] 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.

[8] 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.

[9] 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.

[10] 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.

[11] 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.

[12] 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.

[13] 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.

[14] 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.

[15] 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.