教授
博士生导师
硕士生导师
性别:男
毕业院校:哈尔滨工业大学
学历:博士研究生毕业
学位:工学博士学位
在职信息:在职
所在单位:电气工程学院
入职时间:2001-12-01
办公地点:电力楼516
联系方式:0531-88392587
访问量:
最后更新时间:..
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[21]
李冉.
A distributionally robust model for reserve optimization considering contingency probability uncertainty.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS,
134,
2022.
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[22]
张利.
Feature Selection Method for Non-Intrusive Load Monitoring with Balanced Redundancy.
IEEE transactions on industry applications ,
2021.
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[23]
韩学山.
双馈风电机群并网系统时变最优潮流的优化追踪方法.
《电力自动化设备》,
41,
56,
2021.
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[24]
朱星旭.
A scalable distributed online algorithm for optimal power flow in distribution system.
International Journal of Electrical Power and Energy Systems,
129,
2021.
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[25]
SHAH, AAMER ABBAS.
A Nonlinear Integral Backstepping Controller to Regulate the Voltage and Frequency of an Islanded Microgrid Inverter.
ELECTRONICS,
10,
2021.
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[26]
SHAH, AAMER ABBAS.
A Novel Prediction Error-Based Power Forecasting Scheme for Real PV System Using PVUSA Model: A Grey Box-Based Neural Network Approach.
IEEE Access ,
9,
87196,
2021.
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[27]
叶平峰.
A Novel Thevenin Equivalent Model Considering the Correlation of Source-Grid-Load in Power Systems.
IEEE Access ,
9,
31276,
2021.
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[28]
张利.
Feature Selection Method for Non-intrusive Load Monitoring with Balanced Redundancy and Relevancy.
2020.
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[29]
张利.
Adjustment Oriented Electricity Tariff Recommendation Based on Typical Customers.
2020.
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[30]
张利.
基于设备用电特征的居民电力需求价格弹性评估.
《电力系统自动化》,
44,
48,
2020.
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[31]
王孟夏.
Optimal power flow considering transient thermal behavior of overhead transmission lines.
International Journal of Electrical Power & Energy Systems,
114,
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[32]
王孟夏.
Optimal power flow considering transient thermal behavior of overhead transmission lines.
International Journal of Electrical Power and Energy Systems,
114,
2020.
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[33]
王孟夏.
计及电缆热特性的电热耦合潮流计算.
《电力系统自动化》,
40,
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[34]
王孟夏.
计及输电元件热惯性效应的安全约束最优潮流.
《中国电机工程学报》,
36,
2016.
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[35]
韩学山.
基于设备在线监测的电网状态检修决策模型.
电力系统自动化,
2020.
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[36]
韩学山.
Probabilistic Prediction of Regional Wind Power Based on Spatiotemporal Quantile Regression.
IEEE transactions on industry applications ,
2020.
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[37]
韩学山.
Distributed online optimal power !ow for distribution system.
International Journal of Electrical Power and Energy Systems,
2020.
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[38]
于一潇.
Probabilistic Prediction of Regional Wind Power Based on Spatiotemporal Quantile Regression.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS Journal,
56,
6117,
2020.
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[39]
韩学山.
考虑源网荷关联戴维南等值的解析与辨识.
中国电机工程学报,
2020.
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[40]
朱星旭.
Distributed online optimal power flow for distribution system.
International Journal of Electrical Power and Energy Systems,
120,
2020.
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