李超顺
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个人简历
水电与数字化工程学院院长助理、教授、博士生导师、国家“万人计划”青年拔尖人才。兼任中国振动工程学会转子动力学专委会常务理事、湖北省水力发电工程学会理事。2005年和2010年分别在武汉大学和华中科技大学获得学士和博士学位。学习工作经历:2016.11至今,华中科技大学,教授(破格);2012.11-2016.10,华中科技大学,副教授(破格);2010.7-2012.10,华中科技大学,讲师;2005.9-2010.6,华中科技大学,水利水电工程,博士研究生;2001.9-2005.6,武汉大学,热能与动力工程(水动方向),本科。学术荣誉:(1)入选国家“万人计划”青年拔尖人才(2019);(2)获湖北省杰出青年基金(2019);(3)获全国优秀博士论文提名(2012);主持国家人才项目1项,国家自然科学基金4项、国家重点研发计划专题1项、教育部博士点基金1项,主持企业委托课题多项。近年来主要项目情况:[1]2020-2022,主持国家“万人计划”青年拔尖人才项目“特大型水电机组故障预测与健康管理”;[2]2019-2021,主持湖北省杰出青年基金项目“基于深度学习的大型水电机组故障诊断与性能预测”;[3]2019-2022, 主持国家自然科学基金面上项目“融合深度学习的水电机组故障知识图谱构建与不确定推理诊断”; [4]2018-2020,主持武汉市应用基础前沿专项“融合深度学习的智能电网设备故障知识图谱构建与推理诊断”; [5]2017-2020,主持国家自然科学基金面上项目“抽蓄储能风光互补智能微网多尺度控制研究”;[6]2016-2020,主持国家重点研发计划专题“水电站运行综合优化技术研究;[7]2015-2018,主持国家自然科学基金面上项目“抽水蓄能机组的集成故障诊断非线性预测控制研究”;[8]2012-2014,主持国家自然科学基金青年项目“基于模糊辨识与多模型描述的抽水蓄能机组控制系统故障诊断方法研究”;[9]2012-2014,主持教育部博士点基金项目“基于模糊多模型的水电机组控制系统复杂特征辨识与故障诊断研究”;[10]2011-2012,参与国防973课题“XXX波本征特性研究”(排名2);[11]2013-2013,主持湖北电网委托项目“大规模吸纳外区电力情况下湖北电网调峰能力与调峰措施研究”;[12]2013-2013,主持湖北电网委托项目“湖北电网水火电电源调峰响应能力分析研究”;[13]2011-2012,主持国网电科院南瑞集团委托课题“水轮机空化空蚀状态监测系统研究”;[14]2011-2012,主持国网电科院南瑞集团委托课题“水力发电机组故障诊断及专家辅助决策系统技术开发”;研究成果:在Applied Energy,IEEE TFS, ECM等期刊发表SCI期刊论文60余篇,授权国家发明专利20项,获得省部级一等奖3项、二等奖1项。【奖励】[1] 成果“大型水电机组动力学建模、故障诊断与优化控制”获2017年教育部自然科学奖一等奖;[2]成果“大型水电机组故障诊断与优化控制关键技术及应用”获2015年水力发电科学技术奖一等奖;[3]成果“复杂水电能源多维广义耦合决策系统关键技术及应用”获2010年教育部科技进步奖一等奖;[4]成果“大型抽水蓄能机组调速系统仿真建模、控制优化与性能测试关键技术及应用”获2017年水力发电科学技术奖二等奖;[5]专著《水轮发电机动力学问题及故障诊断原理与方法》获得2015年第四届中国大学出版社图书奖(优秀学术著作)一等奖;[6]博士论文“水电机组控制系统辨识及故障诊断研究”获2012年全国优秀博士论文提名奖;[7]博士论文“水电机组控制系统辨识及故障诊断研究”获2011年湖北省优秀博士论文奖。【部分授权发明专利】(1) 周建中,李超顺,许颜贺,一种中小型水力发电机组的机群等值建模方法,2014. 12-2015.10,中国,201510046939.6。(已授权)(2) 周建中,李超顺,寇攀高,卢有麟,水轮机调速系统仿真测试装置,2011.2-2013 .4,中国,201110044500.1。(已授权)(3) 周建中,黄志伟,李超顺,罗志猛,水力发电机组效率监测装置、系统及方法,2011.2-2012.12,中国,201110044499.2。(已授权)(4) 李超顺,王文潇,汪赞斌,一种混合新能源电力系统机组组合优化方法,中国,201510885235.8。(已授权)(5) 李超顺,赵志高,汪赞斌,一种水轮机调节系统控制参数的优选方法,中国,201510760877.5。(6) 李超顺,董伟,毛翼丰,一种水轮机调节系统的参数辨识方法,中国,201510759863.1。(已授权)(7) 李超顺,张楠,王文潇,一种水轮发电机组励磁系统参数辨识方法,中国,201510760841.7。(已授权)(8) 李超顺,汪赞斌,董伟,一种新能源混合系统控制参数的优选方法,中国,201510160557.X。(已授权)(9) 李超顺,杨兴昭,李如海,一种水轮发电机组励磁系统PID控制参数的优选方法,中国,201510760890.0。(10) 李超顺,周建中,张楠,李如海,毛翼丰,罗萌,一种水轮机调速系统控制参数的自动整定方法,中国,201410811275.3。(11)方仍存,李超顺,李如海,杜治. 基于引力搜索的水火电系统多目标调峰方法,中国,CN201410198218.2。研究领域
(1)水力、风力与光伏发电系统的建模仿真与优化控制;(2)发电设备状态监测、故障诊断与健康管理;(3)新能源电力系统调度、微网的能量管理与控制;(4)大数据、深度学习和人工智能应用研究。"主要从事水电、风电等清洁能源优化运行与控制、发电设备智能维护以及人工智能的应用研究"近期论文
[1] Chaoshun Li*, Geng Tang. Short-term Wind Speed Interval Prediction based on Ensemble GRU model. IEEE Transactions on Sustainable Energy, 2019, doi:10.1109/TSTE.2019.2926147. (一区)[2] Jinjiao Hou, Chaoshun Li*, Wencheng Guo*, et al. Optimal successive start-up strategy of two hydraulic coupling pumped storage units based on multi-objective control. International Journal of Electrical Power and Energy Systems, 2019, 111:398-410. (二区)[3] Wen Zou, Chaoshun Li*, Pengfei Chen. An Inter Type-2 FCR Algorithm Based T-S Fuzzy Model for Short-term Wind Power Interval Prediction. IEEE Transactions on Industrial Informatics, 2019, doi:10.1109/TII.2019.2910606. (一区)[4] Wenlong Fu*, Kai Wang, Chaoshun Li*, Jiawen Tan. Multi-step short-term wind speed forecasting approach based on multi-scale dominant ingredient chaotic analysis, improved hybrid GWO-SCA optimization and ELM. Energy Conversion and Management, 2019, 187:356-377. (一区)[5] Chen Feng, Li Chang*, Chaoshun Li*, Tan Ding, Zijun Mai. Controller Optimization Approach Using LSTM-Based Identification Model for Pumped-Storage Units. IEEE Access, 2019, 7: 32714 - 32727. (二区)[6] Bo Fu, Chenxi Ouyang, Chaoshun Li*, Jinwen Wang, Eid Gul. An improved mixed integer linear programming approach based on symmetry diminishing for unit commitment of hybrid power system. Energies, 2019, 12(5), 833; doi: 10.3390/en12050833.(三区)[7] Chu Zhang, Tian Peng*, Chaoshun Li*, Wenlong Fu, Xin Xia, Xiaoming Xue. Multi-objective optimization of a fractional order PID controller for pumped turbine governing system using an improved NSGA-III algorithm under multi-working conditions. Complexity, 2019, 5826873.(二区)[8] Xinjie Lai, Chaoshun Li*, Jianzhong Zhou, Nan Zhang. Multi-objective optimization for guide vane shutting based on MOASA. Renewable Energy, 2019, 139:302-312.(二区)[9] Xiaoming Xue, Chaoshun Li*, Suqun Cao, Jinchao Sun, Liyan Liu. Fault diagnosis of rolling element bearings with a two-step scheme based on permutation entropy and random forests. Entropy 2019, 21(1), 96; https://doi.org/10.3390/e21010096.[10] Chaoshun Li*, Wenxiao Wang, Deshu Chen. Multi-objective complementary scheduling of Hydro-Thermal-RE power system via a multi-objective hybrid grey wolf optimizer. Energy, 2019, 171: 241-255.(二区)[11] Wenlong Fu*, Kai Wang, Chaoshun Li*, Xiong Li, Yuehua Li, Hao Zhong. Vibration Trend measurement for Hydropower Generator Based on Optimal Variational Mode Decomposition and LSSVM Improved with Chaotic Sine Cosine Algorithm Optimization. Measurement Science and Technology, 2019, 30(1): 015012.2018年[12] Chu Zhang*, Chaoshun Li*, Tian Peng, Xin Xia, Xiaoming Xue, Wenlong Fu, Jianzhong Zhou. Modelling and synchronous optimization of pump turbine governing system using sparse robust least squares support vector machine and hybrid backtracking search algorithm. Energies, 2018, 11(11), 3108; https://doi.org/10.3390/en11113108. [13] Yanhe Xu*, Yang Zheng*, Yi Du, Wen Yang, Xuyi Peng, Chaoshun Li*. Adaptive condition predictive-fuzzy PID optimal control of start-up process for pumped storage unit at low head area, Energy Conversion and Management, 2018, 177: 592-604. (一区)[14] Tan Ding, Li Chang, Chaoshun Li*, Chen Feng, Nan Zhang. A mixed-strategy based whale optimization algorithm for parameter identification of hydraulic turbine governing system with a delay water hammer effect, Energies, 2018, 11(9), 2367; https://doi.org/10.3390/en11092367. [15] Wenlong Fu*, Jiawen Tan, Chaoshun Li*, Zubing Zou, Qiankun Li, Tie Chen. A Hybrid Fault Diagnosis Approach for Rotating Machinery with the Fusion of Entropy-based Feature Extraction and SVM Optimized by Chaos Quantum Sine Cosine Algorithm. Entropy, 2018, 20(9), 626; https://doi.org/10.3390/e20090626. (三区)[16]Jinjiao Hou, Chaoshun Li*, Ziqin Tian, Yanhe Xu*, Xinjie Lai, Nan Zhang, Taoping Zheng and Wei Wu. Multi-Objective Optimization of Start-up Strategy for Pumped Storage Units. Energies 2018, 11(5), 1141; https://doi.org/10.3390/en11051141. (三区)[17]Yanhe Xu, Chaoshun Li*, Zanbin Wang, Nan Zhang, Bing Peng. Load frequency control of a novel renewable energy integrated micro-grid containing pumped hydropower energy storage. IEEE Access, 2018, 6: 29067-29077. (二区)[18] Chaoshun Li*, Zhengguang Xiao, Xin Xia*, Wen Zou, Chu Zhang. A hybrid model based on synchronous optimisation for multi-step short-term wind speed forecasting. Applied Energy, 2018,215:131–144. ( 入选ESI高引)(一区)[19] Xinjie Lai, Chaoshun Li*, Jianzhong Zhou. A Multi-objective Artificial Sheep Algorithm. Neural Comput & Applic, 2018, doi:10.1007/s00521-018-3348-x. (二区)[20] Zanbin Wang, Chaoshun Li*, Xinjie Lai, Nan Zhang, Yanhe Xu*, Jinjiao Hou. An integrated start-up method for pumped storage units based on a novel artificial sheep algorithm. Energies, 2018, 11(1), 151; doi:10.3390/en11010151. (入选ESI高引)[21] Chaoshun Li*, Wen Zou, Nan Zhang, et al. An evolving T-S fuzzy model identification approach based on a special membership function and its application on pump-turbine governing system. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2018, 69: 93-103. (二区)[22] Zou W, Li C*, Zhang N. A T-S Fuzzy Model Identification Approach based on a Modified Inter Type-2 FRCM Algorithm. IEEE Transactions on Fuzzy Systems, 2018, 26(3): 1104 – 1113. (一区)2017年[23] Ruhai Li, Chaoshun Li*. Electromagnetic Vibration Simulation of a 250-MW Large Hydropower Generator with Rotor Eccentricity and Rotor Deformation. Energies, 2017, 10(12), 2155. [24] Xin Xia, Chaoshun Li*, Wei Ni. Dominant low-frequency oscillation modes tracking and parameter optimisation of electrical power system using modified Prony method. IET Generation, Transmission & Distribution, 2017, 11(17): 4358 – 4364. [25] Chaoshun Li*, Zhou J, Chang L, et al. T-S fuzzy model identification based on a novel hyper-plane-shaped membership function. IEEE Transactions on Fuzzy Systems, 2017, 25 (5), 1364-1370. (一区)[26] Chaoshun Li*, Yifeng Mao, Jiandong Yang, et al. A nonlinear generalized predictive control for pumped storage unit. Renewable Energy, 2017, 114:945-959. (二区)[27] Chaoshun Li*, Nan Zhang, Xinjie Lai, Jianzhong Zhou, Yanhe Xu. Design of a fractional order PID controller for a pumped storage unit using a gravitational search algorithm based on the Cauchy and Gaussian mutation. Information Sciences, 2017, 396: 162–181. (入选ESI高引) (二区)[28] Wenxiao Wang, Chaoshun Li*, Xiang Liao, Hui Qin. Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm. Applied Energy, 2017, 187: 612–626. (一区)[29] Chaoshun Li*, Yifeng Mao, Jianzhong Zhou, Nan Zhang, Xueli An. Design of a fuzzy-PID controller for a nonlinear hydraulic turbine governing system by using a novel gravitational search algorithm based on Cauchy mutation and mass weighting. Applied Soft Computing, 2017, 52: 290-305. (二区)2016年及以前[30] Meng Luo, Chaoshun Li*, Xiaoyuan Zhang, Ruhai Li, Xueli An. Compound feature selection and parameter optimization of ELM for fault diagnosis of rolling element bearings. ISA Transactions, 2016, 65: 556-566. (二区)[31] Nan Zhang, Chaoshun Li*, Ruhai Li, Xinjie Lai, Yuanchuan Zhang. A mixed-strategy based gravitational search algorithm for parameter identification of hydraulic turbine governing system. Knowledge-Based Systems, 2016, 109: 218-237. (二区)[32] Chaoshun Li*, Li Chang, Zhengjun Huang, et al. Parameter identification of a nonlinear model of hydraulic turbine governing system with an elastic water hammer based on a modified gravitational search algorithm. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2016, 50: 177-191. (二区)[33] Chaoshun Li*, Xueli An, Ruhai Li. A chaos embedded GSA-SVM hybrid system for classification.Neural Comput & Applic, 2015, 26(3): 713–721. (IF: 1.492) (二区)[34] Chaoshun Li*, Hongshun Li, Pangao Kou, Piecewise function based gravitational search algorithm and its application on parameter identification of AVR system, Neurocomputing, 2014, 124: 139-148. (二区)[35] Chaoshun Li*, Jianzhong Zhou. Semi-supervised weighted kernel clustering based on gravitational search for fault diagnosis. ISA Transactions, 2014, 53(5): 1534-1543. (IF: 2.6) (二区)[36] Chaoshun Li*, Jianzhong Zhou, Jian Xiao, Han Xiao, Hydraulic turbine governing system identification using T–S fuzzy model optimized by chaotic gravitational search algorithm, Engineering Applications of Artificial Intelligence, 2013, 26 (9), 2073-2082. (二区)[37] Chaoshun Li*, Jianzhong Zhou, Bo Fu, Pangao Kou, Jian Xiao, T-S fuzzy model identification with gravitational search based hyper-plane clustering algorithm, IEEE Transactions on Fuzzy Systems, 2012, 20 (2): 305-317. (一区)[38] Chaoshun Li*, Jianzhong Zhou, Jian Xiao, Han Xiao, Parameters identification of chaotic system by chaotic gravitational search algorithm, Chaos, Solitons & Fractals 45 (4), 2012, 539-547. [39] Chaoshun Li*, Jianzhong Zhou, Pangao Kou, Jian Xiao, A novel chaotic particle swarm optimization based fuzzy clustering algorithm, Neurocomputing, 2012, 83: 98-109. (二区)[40] Chaoshun Li, Jianzhong Zhou*, Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm, Energy Conversion and Management, 2011, 52 (1), 374-381. (入选ESI高引) (一区)[41] Chaoshun Li, Jianzhong Zhou*, Qingqing Li, et.al. A new T-S fuzzy-modeling approach to identify a boiler–turbine system. Expert Systems with Applications, 2010, 37(3): 2214-2221. (二区)[42]Chaoshun Li, Jianzhong Zhou*, Xiuqiao Xiang, Qingqing Li, Xueli An. T-S fuzzy model identification based on a novel fuzzy c-regression model clustering algorithm. Engineering Applications of Artificial Intelligence, 2009, 22(4-5): 646-653 (IF: 2.368) (二区)标签: 华中科技大学 水电与数字化工程学院
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