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《Automation of Electric Power Systems》 1992-05
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OPTIMAL REACTIVE POWER CONTROL USING HOPFIELD MODEL

Chen Wcnhui, Yan Junjing, Dai Wcnxiang (Shanghai Jiao Tong University)  
This paper presents an ANN method for the optimal reactive power control. The method is based on the Hopfield model which is used to solve the optimal reactive power compensation in this paper. It has been tested on IEEE-6 and IEEE-30 node systems and achieved a satisfactory result.
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【References】
Chinese Journal Full-text Database 2 Hits
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【Citations】
Chinese Journal Full-text Database 1 Hits
1 Wen Fushuan Han Zhenxiang (Dept. of E. E., Zhejiang University);THE OPTIMAL DISTRIBUTION OF REACTIVE POWER SOURCES IN POWER SYSTEMS BASED UPON HOPFIELD CONTINUOUS MODEL[J];Proceedings of Electric Power System and Automation;1990-02
【Co-citations】
Chinese Journal Full-text Database 3 Hits
1 Wu Xiuhua (Shenyang Agricultural Un iversity);Summary on Application of Neural Network in Reactive Power Optimization[J];Electrotechnical Application;2007-09
2 Wen Fushuan;Han Zhenxiang Dept.of Electrical Engineering,Zhejiang University;ECONOMICAL LOAD DISPATCHING IN HYDRO-THERMAL POWER SYSTEMS—THE APPLICATION OF HOPFIELD CONTINUOUS MODEL[J];Proceedings of Electric Power System and Automation;1991-01
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Chinese Journal Full-text Database 10 Hits
1 Liu Hongchao,Peng Jianchun,Li Shengwei,Ouyang Zhengwu(College of Electricity & Information Engineering of Hunan University,Changsha 410082,China);A summary of reactive power control and optimization in power system[J];Electrical Measurement & Instrumentation;2004-04
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【Secondary References】
Chinese Journal Full-text Database 2 Hits
1 Kang Jitao (Southwest Jiaotong University);Reactive Power Optimization of Power System Using Improved Adaptive Genetic Algorithm[J];Electrotechnical Application;2006-10
2 ZHANG Yu-nong1,MAI Jian-zhang2,XIAO Xiu-chun1,LI Zhan1,YI Chen-fu1(1.Department of Electronics and Communication Engineering,Sun Yat-Sen University,Guangzhou 510275 China;2.School of Software,Sun Yat-Sen University,Guangzhou 510275 China);The Common Nature of Learning of the BP and Hopfield-type Neural Networks in the Minimization of Quadratic Functions[J];Techniques of Automation and Applications;2008-09
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