Voltage Sag State Estimation Based on Hybrid Particle Swarm Optimization Algorithm

被引:0
作者
Fan Di [1 ]
Tian Lijun [1 ]
Cui Yu [2 ]
机构
[1] Shandong Univ, Sch Elect Engn, Jinan 250061, Peoples R China
[2] Jiangsu Elect Power Co, State Grid Corp China, Nanjing 210024, Jiangsu, Peoples R China
来源
PROCEEDINGS OF THE 2015 10TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS | 2015年
关键词
power quality; voltage sag; state estimation; hybrid particle swarm optimization algorithm; optimal allocation; round-off method;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper presents an approach applying Hybrid Particle Swarm Optimization algorithm to voltage sag frequency state estimation, based on the monitoring system determined by optimum allocation method of voltage sag monitoring nodes. Voltage sag frequency state estimation is interpreted as the estimation of the number of voltage sags occurring at non-monitored buses from the recorded voltage sags occurrence number at the monitored buses. In this study, a Hybrid Particle Swarm Optimization algorithm is proposed to solve the problem of voltage sag state estimation by the use of round-off method. The effectiveness and accuracy of the proposed approach are verified by the case study of the IEEE-39 standard test system.
引用
收藏
页码:1729 / 1734
页数:6
相关论文
共 50 条
[31]   Enhancement of state estimation power system based hybrid algorithm [J].
Hussein, Mothafer A. ;
Sultan, Ahmed Jasim .
2018 1ST ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION AND SCIENCES (AICIS 2018), 2018, :164-169
[32]   Fault location estimation based on voltage sag information of PQMS [J].
Zhao C. ;
Tao S. ;
Xiao X. .
Dianwang Jishu/Power System Technology, 2016, 40 (02) :642-648
[33]   Fault Location Estimation Based on Voltage Sag Information of PQMS [J].
Tao, Shun ;
Zhao, Chenxue ;
Luo, Chen ;
Xiao, Xiangning .
2015 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2015,
[34]   Multi-Stage Voltage Sag State Estimation Using Event-Deduction Model Corresponding to EF, EG, and EP [J].
Wang, Ying ;
He, Hai-Shan ;
Xiao, Xian-Yong ;
Li, Shun-Yi ;
Chen, Yun-Zhu ;
Ma, Hai-Xing .
IEEE TRANSACTIONS ON POWER DELIVERY, 2023, 38 (02) :797-811
[35]   Weighted Least Squares and Iteratively Reweighted Least Squares Comparison using Particle Swarm Optimization Algorithm in Solving Power System State Estimation [J].
Tungadio, D. H. ;
Numbi, B. P. ;
Siti, M. W. ;
Jordaan, J. A. .
AFRICON, 2013, 2013, :1265-1270
[36]   Estimation of Transmission Lines Parameters Using Particle Swarm Optimization [J].
Cabezas Soldevilla, Fermin Rafael ;
Cabezas Huerta, Franklin Alfredo .
PROCEEDINGS OF THE 2018 IEEE PES TRANSMISSION & DISTRIBUTION CONFERENCE AND EXHIBITION - LATIN AMERICA (T&D-LA), 2018,
[37]   Power System Harmonics Estimation using Particle Swarm Optimization [J].
Rabelo, Ricardo de A. L. ;
Lemos, Marcus V. ;
Barbosa, Daniel .
2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2012,
[38]   Voltage sag state estimation for power distribution systems using Kalman filter [J].
Janabali, Mahda ;
Meshksar, Sina ;
Farjah, Ebrahim ;
Zolghadri, Mansour .
2007 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS, PROCEEDINGS, VOLS 1-8, 2007, :2449-2453
[39]   Optimal EV Placement using Particle Swarm Optimization Algorithm [J].
Neethu, V. S. ;
Jyothi, N. S. ;
Deshpande, Raghavendraprasad .
2021 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, COMMUNICATION, COMPUTER TECHNOLOGIES AND OPTIMIZATION TECHNIQUES (ICEECCOT), 2021, :267-272
[40]   METHODOLOGY BASED ON ADABOOST ALGORITHM COMBINED WITH NEURAL NETWORK FOR THE LOCATION OF VOLTAGE SAG DISTURBANCE [J].
Borges, F. A. S. ;
Rabelo, R. A. L. ;
Fernandes, R. A. S. ;
Araujo, M. A. .
2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2019,