Non-invasive identification of turbo-generator parameters from actual transient network data

被引：11

作者：

Hutchison, Greame ^{[1
]}

Zahawi, Bashar ^{[2
]}

Harmer, Keith ^{[1
]}

Gadoue, Shady ^{[3
,4
]}

Giaouris, Damian ^{[5
]}

机构：

[1] Parsons Brinckerhoff, Newcastle Upon Tyne NE4 7YQ, Tyne & Wear, England

[2] Khalifa Univ, Dept Elect & Comp Engn, Abu Dhabi 127788, U Arab Emirates

[3] Newcastle Univ, Sch Elect & Elect Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England

[4] Univ Alexandria, Fac Engn, Dept Elect Engn, Alexandria 21544, Egypt

[5] Ctr Res & Technol Hellas, Chem Proc Engn Res Inst, Thessaloniki 57001, Greece

来源：

IET GENERATION TRANSMISSION & DISTRIBUTION | 2015年 / 9卷 / 11期

关键词：

PARTICLE SWARM OPTIMIZATION; SYNCHRONOUS MACHINE; MODEL;

D O I：

10.1049/iet-gtd.2014.0481

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Synchronous machines are the most widely used form of generators in electrical power systems. Identifying the parameters of these generators in a non-invasive way is very challenging because of the inherent non-linearity of power station performance. This study proposes a parameter identification method using a stochastic optimisation algorithm that is capable of identifying generator, exciter and turbine parameters using actual network data. An eighth order generator/turbine model is used in conjunction with the measured data to develop the objective function for optimisation. The effectiveness of the proposed method for the identification of turbo-generator parameters is demonstrated using data from a recorded network transient on a 178 MVA steam turbine generator connected to the UK's national grid.

引用

页码：1129 / 1136

页数：8

共 25 条

[1]

[Anonymous], 1973, IEEE T POWER AP SYST, VPA92, P1904, DOI 10.1109/TPAS.1973.293570

[2] Parameter Estimation of a Synchronous Generator Using a Sine Cardinal Perturbation and Mixed Stochastic-Deterministic Algorithms [J].

Arjona, M. A. ;

Cisneros-Gonzalez, M. ;

Hernandez, C. .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2011, 58 (02) :486-493

[3] Multiphysics Modeling of a Permanent Magnet Synchronous Machine by Using Lumped Models [J].

Bracikowski, Nicolas ;

Hecquet, Michel ;

Brochet, Pascal ;

Shirinskii, Sergey V. .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2012, 59 (06) :2426-2437

[4]

Clerc M., 2006, Particle Swarm Optimization

[5] VALIDATION OF TURBOGENERATOR STABILITY MODELS BY COMPARISONS WITH POWER SYSTEM TESTS [J].

DANDENO, PL ;

KUNDUR, P ;

PORAY, AT ;

COULTES, ME .

IEEE TRANSACTIONS ON POWER APPARATUS AND SYSTEMS, 1981, 100 (04) :1637-1645

[6] Particle swarm optimization: Basic concepts, variants and applications in power systems [J].

del Valle, Yamille ;

Venayagamoorthy, Ganesh Kumar ;

Mohagheghi, Salman ;

Hernandez, Jean-Carlos ;

Harley, Ronald G. .

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2008, 12 (02) :171-195

[7] DYNAMIC-MODELS FOR FOSSIL FUELED STEAM UNITS IN POWER-SYSTEM STUDIES [J].

DEMELLO, FP .

IEEE TRANSACTIONS ON POWER SYSTEMS, 1991, 6 (02) :753-761

[8] Particle Swarm Design Optimization of Transverse Flux Linear Motor for Weight Reduction and Improvement of Thrust Force [J].

Hasanien, Hany M. .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2011, 58 (09) :4048-4056

[9] Online Synchronous Machine Parameter Extraction From Small-Signal Injection Techniques [J].

Huang, Jing ;

Corzine, Keith A. ;

Belkhayat, Mohamed .

IEEE TRANSACTIONS ON ENERGY CONVERSION, 2009, 24 (01) :43-51

[10] A Deterministic Particle Swarm Optimization Maximum Power Point Tracker for Photovoltaic System Under Partial Shading Condition [J].

Ishaque, Kashif ;

Salam, Zainal .

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2013, 60 (08) :3195-3206

← 1 2 3 →