寇鵬，男，博士，西安交通大學教授，主要作品有《含混合式配電變壓器的主動配電網電壓魯棒模型預測控制》等。
基本介紹
- 中文名：寇鵬
- 學位/學歷：博士
- 職業：教師
- 專業方向：Power system prediction and control Predictive control等
- 職稱：教授
- 任職院校：西安交通大學
個人經歷,研究方向,學術成果,
個人經歷
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 a professor at the school of electrical engineering, Xi’an Jiaotong University.
Academic Activities
IEEE senior member, since 2019
IEEE member, 2014-2019
IEEE student member, 2008-2013
Faculty member of the Shaanxi Key Laboratory of Smart Grid
Reviewer for the projects of National Natural Science Foundation of China.
研究方向
Research Interests
Power system prediction and control
Predictive control
Renewable energy and smart grid
Machine learning
學術成果
Projects
Cooperative distributed predictive control of multiple PMSGs in dc microgrid, National Natural Science Foundation of China (NSFC 51777162), principle investigator.
Wind farm frequency support using distributed control, Shaanxi Electric Power Research Academy - State Grid, principle investigator.
Frequency support from a dc-grid offshore wind farm connected through HVDC link, Xi'an Jiaotong University, principle investigator.
Coordinated control of multi-functional synchronous condenser, Shandong Electric Power Research Academy - State Grid, 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.
Reviewer for IEEE Transactions on Power systems, IEEE Transactions on Energy Conversion, IEEE Transactions on Smart Grid, IEEE Transactions on Industrial Informaticas, IEEE Transactions on Industrial Informatics, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Neural Networks and Learning systems, IEEE Systems Journal, Applied Energy, Energy Conversion and Management, Control Engineering Practice, Systems & Control Letters, Neurocomputing, IET Generation, Transmission & Distribution, IET Renewable Power Generation, Wind Energy, International Journal of Electrical Power and Energy Systems, Journal of Energy Engineering, 2016 IEEE Power and Energy Society General Meeting, 2017 IEEE Power and Energy Society General Meeting, IECON 2016, 31st. Chinese Control Conference.
Publication
Profiles at Google scholar: https://scholar.google.com/citations?user=WZhRnbwAAAAJ&hl=en
Journal Papers:
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, Accepted.
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.
高榮, 寇鵬*, 梁得亮, 柳軼彬, 吳子豪, 含混合式配電變壓器的主動配電網電壓魯棒模型預測控制, 中國電機工程學報, accepted.
王晨, 寇鵬*, 基於卷積神經網路和簡單循環單元集成模型的風電場內多風機風速預測, 電工技術學報, accepted.
虞臨波, 寇鵬*,馮玉濤, 馮浩天, 風儲聯合發電系統參與頻率回響的模型預測控制策略, 電力系統自動化, vol. 43, no. 12, pp. 36-43, 2019.
寇鵬*, 高峰, 幾何轉換Boosting回歸算法及其在高耗能企業負荷預測中的套用, 系統工程理論與實踐, vol. 33, no. 7, pp. 1880-1888, 2013.
范伯良, 高峰, 寇鵬*, 線上Boosting回歸算法及其在高耗能企業負荷預測中的套用, 信息與控制, 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.
