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

页码：1729 / 1734

页数：6

共 50 条

[21] A novel adaptive wavelet threshold estimation based on hybrid particle swarm optimization for partial discharge signal denoising [J].

Si, Wen ;

Qin, Bingyang ;

Li, Qingquan ;

Liu, Hongshun .

OPTIK, 2019, 181 :175-184

[22] A Gaussian Particle Swarm Optimization-Based Phase Unwrapping Algorithm [J].

Li, Rong ;

Xie, Xianming .

IEEE JOURNAL ON MINIATURIZATION FOR AIR AND SPACE SYSTEMS, 2023, 4 (01) :9-17

[23] Particle Swarm Optimization and Genetic Algorithm based Harmonic Mitigation methods [J].

Kumar, K. S. Ravi ;

Divya, V. ;

Prasanna, N. S. .

IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, DRIVES AND ENERGY SYSTEMS (PEDES 2012), 2012,

[24] Key Frames Extraction from Human Motion Capture Data Based on Hybrid Particle Swarm Optimization Algorithm [J].

Chang, Xiaojing ;

Yi, Pengfei ;

Zhang, Qiang .

RECENT DEVELOPMENTS IN INTELLIGENT INFORMATION AND DATABASE SYSTEMS, 2016, 642 :335-342

[25] Intelligent bearing fault diagnosis using swarm decomposition method and new hybrid particle swarm optimization algorithm [J].

Chegini, Saeed Nezamivand ;

Amini, Pouriya ;

Ahmadi, Bahman ;

Bagheri, Ahmad ;

Amirmostofian, Illia .

SOFT COMPUTING, 2022, 26 (03) :1475-1497

[26] Intelligent bearing fault diagnosis using swarm decomposition method and new hybrid particle swarm optimization algorithm [J].

Saeed Nezamivand Chegini ;

Pouriya Amini ;

Bahman Ahmadi ;

Ahmad Bagheri ;

Illia Amirmostofian .

Soft Computing, 2022, 26 :1475-1497

[27] Time-Domain Voltage Sag State Estimation Based on the Unscented Kalman Filter for Power Systems with Nonlinear Components [J].

Cisneros-Magana, Rafael ;

Medina, Aurelio ;

Anaya-Lara, Olimpo .

ENERGIES, 2018, 11 (06)

[28] Voltage sag state estimation based on l(1)-norm minimization methods in radial electric power distribution systems [J].

Blanco-Solano, Jairo ;

Kagan, Nelson ;

Almeida, Carlos Frederico M. ;

Petit-Suarez, Johann F. ;

Ordonez-Plata, Gabriel .

UIS INGENIERIAS, 2018, 17 (02) :309-317

[29] Fault detection and identification for voltage sag state estimation in power systems [J].

Beiza, Jamal ;

Hosseinian, Seyed Hossein ;

Vahidi, Behrooz .

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, 2010, 18 (04) :665-675

[30] Computation of Voltage Sag Initiation with Fourier based Algorithm, Kalman Filter and Wavelets [J].

Amaris, H. ;

Alvarez, C. ;

Alonso, M. ;

Florez, D. ;

Lobos, T. ;

Janik, P. ;

Rezmer, J. ;

Waclawek, Z. .

2009 IEEE BUCHAREST POWERTECH, VOLS 1-5, 2009, :1111-+

← 1 2 3 4 5 →