Basic Data

 

寇鹏 副教授

Kou Peng

Associate Professor, Ph.D

IEEE Senior Member

Ph.D Supervisor

School of Electrical Engineering

Xi'an Jiaotong University

Contact

Office: East Room 110 , East 1# Building

Email: koupeng(AT)mail.xjtu.edu.cn

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Education

I received my B.S. degree in electrical engineering from Xi’an Jiaotong University, China, in 2005. From the same university, I received my M.S. and Ph.D. degrees in control science and engineering in 2008 and 2013, respectively. From Nov. 2015 to Nov. 2016, I worked as a visiting scholar at The Ohio State University in Columbus, OH, US.

Currently I am an associate professor at the school of electrical engineering, Xi’an Jiaotong University.

Research Interests

Power system prediction and control

Predictive control

Renewable energy and smart grid

Distributed electric propulsion aircraft

Machine learning

 

Graduate Opportunities

Dr. Kou is currently accepting Ms and PhD students in the field of renewable energy system control, smart grid control, and machine learning. Applicants who are self-motivated and interested in these research areas are welcomed to apply.

Projects

  • Powered yaw control of distributed electric propulsion aircraft, XXXX Innovation Zone, principle investigator.
  • Cooperative predictive control of wind generators in all-dc offshore wind farm to provide frequency response, National Natural Science Foundation of China (NSFC 52077165), principle investigator.
  • Cooperative distributed predictive control of multiple PMSGs in dc microgrid, National Natural Science Foundation of China (NSFC 51777162), principle investigator.
  • Frequency support from a dc-grid offshore wind farm connected through HVDC link, Xi'an Jiaotong University, principle investigator.
  • Stochastic predictive control of wind-ESS system: using online probabilistic wind power forecasts, National Natural Science Foundation of China (NSFC 61403303), principle investigator.
  • Distributed economic predictive control of multi-microgrids considering the supply and demand uncertainties, Special Financial Grant from the China Postdoctoral Science Foundation (2016T90918), principle investigator.
  • Stochastic coordinated predictive control of DFIG based wind-battery hybrid systems, China Postdoctoral Science Foundation funded project (2014M560776), principle investigator.
  • Stochastic synergistic control of PEVs and wind power with dual uncertainties, Natural Science Basis Research Plan in Shaanxi Province of China (2016JQ5080), principle investigator.
  • Synchronization control of multi-PMSM systems using FCS-MPC, State Key Laboratory of Electrical Insulation and Power Equipment funded project (EIPE15306), principle investigator.
  • Collaborative design and redundancy optimal control of multiple-electric machine system with energy storage units, National Natural Science Foundation of China (NSFC 51737010), team member.

 

  • Coordinated control of distributed renewable energy and energy storage system, Shandong Electric Power Research Academy - State Grid, principle investigator.
  • Modeling and simulation of renewable energy system, Shaanxi Electric Power Research Academy - State Grid, principle investigator.
  • Compound perception of critical power equipment statues, State Grid, principle investigator.
  • Adaptive control of compressor in refrigerator, Sichuan HOMME, principle investigator.
  • Wind farm frequency support using distributed control, Shaanxi Electric Power Research Academy - State Grid, principle investigator.
  • Coordinated control of multi-functional synchronous condenser, Shandong Electric Power Research Academy - State Grid, principle investigator.
  • Simplified eccentric sensing technoglogy for rollers, Wuxi Little Swan Co., principle investigator.

 

Academic Activities

IEEE senior member

 

Faculty member of the Shaanxi Key Laboratory of Smart Grid

 

Reviewer for the projects of National Natural Science Foundation of China
Reviewer for IEEE Transactions on Power Systems, IEEE Transactions on Energy Conversion, IEEE Transactions on Smart Grid, IEEE Transactions on Sustainable Energy, IEEE Transactions on Power Electronics, IEEE Transactions on Industrial Electronics, IEEE Transactions on Industrial Informatics, IEEE Transactions on Control Systems Technology, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Neural Networks and Learning systems, IEEE Systems Journal, Applied Energy, Energy Conversion and Management, Neurocomputing, IET Generation, Transmission & Distribution, IET Renewable Power Generation, IET Smart Grid, Wind Energy, International Journal of Electrical Power and Energy Systems, Systems & Control Letters, Control Engineering Practice

Publications

Profiles at Google scholar: https://scholar.google.com/citations?user=WZhRnbwAAAAJ&hl=en

Journal Papers:

Yuanhang Zhang, Peng Kou*, Linbo Yu, and Deliang Liang , Coordinated voltage and frequency control for HVDC sending end under pole-block fault: using model predictive controlInternational Journal of Electrical Power and Energy SystemsAccepted.

Peng Kou*, Jing Wang, and Deliang Liang, Powered yaw control for distributed electric propulsion aircraft: a model predictive control approachIEEE Transactions on Transportation Electrificationvol. 7, no. 4, pp. 3006-3020, 2021.

Rong Gao, Peng Kou*, Deliang Liang, and Chuankai Yang, Optimal allocation of hybrid distribution transformers considering dynamical controlInternational Journal of Electrical Power and Energy Systemsvol. 131, no. 11, pp. 107052, 2021.

Peng Kou*, Deliang Liang, Rong Gao, Chuankai Yang, and Lin Gao, Optimal placement and sizing of reactive power sources in active distribution networks: a model predictive control approach, IEEE Transactions on Sustainable Energyvol. 12, no. 2, pp. 966-977, 2021.
Peng Kou*,
 Deliang Liang, Rong Gao, Yibin Liu, and Lin Gao, Decentralized model predictive control of hybrid distribution transformers for voltage regulation in active distribution networks, IEEE Transactions on Sustainable Energy vol. 11, no. 4, pp. 2189-2200, 2020.
Peng Kou*, Chen Wang, Deliang Liang, Song Cheng, and Lin Gao, A deep learning approach for wind speed forecasts at turbine locations in a wind farm, IET Renewable Power Generation, vol. 14, no. 13, pp. 2416-2428, 2020.
Peng Kou*, Deliang Liang, Chen Wang, Zihao Wu, and Lin Gao, Safe deep reinforcement learning-based constrained optimal control scheme for active distribution networks, Applied Energy, vol. 264, no. 4, pp. 114772, 2020.
Peng Kou*, Deliang Liang, Linbo Yu, and Lin Gao, Nonlinear model predictive control of wind farm for system frequency support, IEEE Transactions on Power Systems vol. 34, no. 5, pp. 3547-3561, 2019.
Peng Kou*, Yutao Feng, Deliang Liang, and Lin Gao, A model predictive control approach for matching uncertain wind generation with PEV charging demand in a microgrid, International Journal of Electrical Power and Energy Systems, vol. 105, no. 2, pp. 488-499, 2019.
Peng Kou*, Deliang Liang, Zihao Wu, Qiji Ze, and Lin Gao, Frequency support from a DC-grid offshore wind farm connected through HVDC link: a communication free approach, IEEE Transactions on Energy Conversion, vol. 33, no. 3, pp. 1297-1310, 2018.
Peng Kou*, Deliang Liang, Junmin Wang, and Lin Gao, Stable and optimal load sharing of multiple PMSGs in an islanded DC microgrid, IEEE Transactions on Energy Conversion, vol. 33, no. 1, pp. 260-271, 2018.
Peng Kou*, Deliang Liang, Jing Li, Lin Gao, and Qiji Ze, Finite-control-set model predictive control for DFIG wind turbines, IEEE Transactions on Automation Science and Engineering, vol. 15, no. 3, pp. 1004-1013, 2018.
Peng Kou*, Deliang Liang, and Lin Gao, Stochastic energy scheduling in microgrids considering the uncertainties in both supply and demand, IEEE Systems Journal, vol. 12, no. 3, pp. 2589-2600, 2018.
Peng Kou*, Deliang Liang, and Lin Gao, Distributed coordination of multiple PMSGs in an islanded dc microgrid for load sharing, IEEE Transactions on Energy Conversion, vol. 32, no. 2, pp. 471-485, 2017.
Peng Kou*, Deliang Liang, and Lin Gao, Distributed EMPC of multiple microgrids for coordinated stochastic energy management, Applied Energy, vol. 185, no. 1, pp. 939-952, 2017. (
ESI Highly Cited Paper)
Peng Kou*, Deliang Liang, Lin Gao, and Feng Gao, Stochastic coordination of plug-in electric vehicles and wind turbines in microgrid: a model predictive control approach, IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1537-1551, 2016.
Peng Kou*, Deliang Liang, Feng Gao, and Lin Gao, Coordinated predictive control of DFIG-based wind-battery hybrid systems: using non-Gaussian wind power predictive distributions, IEEE Transactions on Energy Conversion, vol. 30, no. 2, pp. 681-695, 2015.
Peng Kou*, Feng Gao, and Xiaohong Guan, Stochastic predictive control of battery energy storage for wind farm dispatching: using probabilistic wind power forecasts, Renewable Energy, vol. 80, no. 8, pp. 286-300, 2015. 
Peng Kou*, Deliang Liang, Lin Gao, and Jianyong Lou, Probabilistic electricity price forecasting with variational heteroscedastic Gaussian process and active learning, Energy Conversion and Management, vol. 89, no. 1, pp. 298-308, 2015. 
Peng Kou*, Deliang Liang, Feng Gao, and Lin Gao, Probabilistic wind power forecasting with online model selection and warped Gaussian process, Energy Conversion and Management, vol. 84, no. 8, pp. 649-663, 2014.
Peng Kou*, Feng Gao, Sparse Gaussian process regression model based on L1/2 regularization, Applied Intelligence, vol. 40, no. 4, pp. 669-681, 2014.
Peng Kou*, Feng Gao, A sparse heteroscedastic model for the probabilistic load forecasting in energy-intensive enterprises, International Journal of Electrical Power and Energy Systems, vol. 55, no. 2, pp. 144-154, 2014. 
Peng Kou*, Feng Gao, and Xiaohong Guan, Sparse online warped Gaussian process for wind power probabilistic forecasting, Applied Energy, vol. 108, no. 8, pp. 410-428, 2013.
Feng Gao, Peng Kou*, Lin Gao and Xiaohong Guan, Boosting regression methods based on a geometric conversion approach: using SVMs base learners, Neurocomputing, vol. 113, no. 8, pp. 67-87, 2013.
王晨寇鹏*, 王若谷, 高欣, 利用多空间尺度下时空相关性的点云分布多风机风速预测, 电力系统自动化, accepted.

高荣寇鹏*, 梁得亮, 柳轶彬, 吴子豪, 含混合式配电变压器的主动配电网电压鲁棒模型预测控制, 中国电机工程学报, vol. 40, no. 7, pp. 2081-2090, 2020.
王晨寇鹏*, 基于卷积神经网络和简单循环单元集成模型的风电场内多风机风速预测, 电工技术学报, vol. 35, no. 13, pp. 2723-2735, 2020.
虞临波寇鹏*,冯玉涛, 冯浩天风储联合发电系统参与频率响应的模型预测控制策略, 电力系统自动化, vol. 43, no. 12, pp. 36-43, 2019.
寇鹏*, 高峰, 几何转换Boosting回归算法及其在高耗能企业负荷预测中的应用, 系统工程理论与实践, vol. 33, no. 7, pp. 1880-1888, 2013. 
范伯良, 高峰寇鹏*, 在线Boosting回归算法及其在高耗能企业负荷预测中的应用, 信息与控制, vol. 43, no. 6, pp. 750-756, 2014.

Conference papers

Peng Kou*, Deliang Liang, and Junmin Wang, “Stable coordination of multiple PMSGs in an islanded dc microgrid: a distributed model predictive control approach,” in Proc. the 56th IEEE Conference on Decision and Control (CDC), Melbourne, Australia, 2017.
Peng Kou*, Deliang Liang, and Lin Gao, “Stochastic model predictive control for wind turbines with doubly fed induction generators,” in Proc. 2016 IEEE Power & Energy Society General Meeting (PES GM), Boston, MA, USA, 2016.
Peng Kou*, Feng Gao, Xiaohong Guan and Jiang Wu, “Prediction intervals for wind power forecasting: using sparse warped Gaussian process,” in Proc. 2012 IEEE Power & Energy Society General Meeting (PES GM), San Diego, CA, USA, 2012.
Peng Kou* and Feng Gao, “Sparse heteroscedastic Gaussian process for short-term wind speed forecasting,” in Proc. 2012 IEEE International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, 2012.
Peng Kou*, Feng, Gao, Lin Gao, “A geometric conversion approach for boosting regression problem,” in Proc. of 2nd International Conference on Computer Engineering and Technology (ICCET), 2010, April, Chengdu, China. pp. 595-599.
Lin Gao, Peng Kou*, Feng Gao, Xiaohong Guan, “AdaBoost regression algorithm based on classification-type loss”, in Proc. of 8th World Congress on Intelligent Control and Automation (WCICA), 2010, July, Jinan, China.