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Frontiers of Electrical and Electronic Engineering

ISSN 2095-2732

ISSN 2095-2740(Online)

CN 10-1028/TM

Front Elect Electr Eng    2012, Vol. 7 Issue (4) : 416-426    https://doi.org/10.1007/s11460-012-0219-6
RESEARCH ARTICLE
Improving power system dynamic performance using attuned design of dual-input PSS and UPFC PSD controller
Yashar HASHEMI, Rasool KAZEMZADEH(), Mohammad Reza AZIZIAN, Ahmad SADEGHI YAZDANKHAH
Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran
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Abstract

The objective of this work is the coordinated design of controllers that can enhance damping of power system swings. With presence of flexible AC transmission system (FACTS) device as unified power flow controller (UPFC), three specific classes of the power system stabilizers (PSSs) have been investigated. The first one is a conventional power system stabilizer (CPSS); the second one is a dual-input power system stabilizer (dual-input PSS); and the third one is an accelerating power PSS model (PSS2B). Dual-input PSS and PSS2B are introduced to maintain the robustness of control performance in a wide range of swing frequency. Uncoordinated PSS and UPFC damping controller may cause unwanted interactions; therefore, the simultaneous coordinated tuning of the controller parameters is needed. The problem of coordinated design is formulated as an optimization problem, and particle swarm optimization (PSO) algorithm is employed to search for optimal parameters of controllers. Finally, in a system having a UPFC, comparative analysis of the results obtained from application of the dual-input PSS, PSS2B, and CPSS is presented. The eigenvalue analysis and the time-domain simulation results show that the dual-input PSS & UPFC and the PSS2B & UPFC coordination provide a better performance than the conventional single-input PSS & UPFC coordination. Also, the PSS2B & UPFC coordination has the best performance.

Keywords simultaneous coordinated design      unified power flow controller (UPFC)      power swing damping (PSD)      dual-input power system stabilizer     
Corresponding Author(s): KAZEMZADEH Rasool,Email:r.kazemzadeh@sut.ac.ir   
Issue Date: 05 December 2012
 Cite this article:   
Yashar HASHEMI,Rasool KAZEMZADEH,Mohammad Reza AZIZIAN, et al. Improving power system dynamic performance using attuned design of dual-input PSS and UPFC PSD controller[J]. Front Elect Electr Eng, 2012, 7(4): 416-426.
 URL:  
https://academic.hep.com.cn/fee/EN/10.1007/s11460-012-0219-6
https://academic.hep.com.cn/fee/EN/Y2012/V7/I4/416
Fig.1  A single machine connected to infinite bus with UPFC
Fig.1  A single machine connected to infinite bus with UPFC
Fig.1  A single machine connected to infinite bus with UPFC
Fig.1  A single machine connected to infinite bus with UPFC
Fig.1  A single machine connected to infinite bus with UPFC
Fig.2  Structure of UPFC-based damping controller
Fig.2  Structure of UPFC-based damping controller
Fig.2  Structure of UPFC-based damping controller
Fig.2  Structure of UPFC-based damping controller
Fig.2  Structure of UPFC-based damping controller
Fig.3  Dual-input PSS
Fig.3  Dual-input PSS
Fig.3  Dual-input PSS
Fig.3  Dual-input PSS
Fig.3  Dual-input PSS
Fig.4  PSS2B
Fig.4  PSS2B
Fig.4  PSS2B
Fig.4  PSS2B
Fig.4  PSS2B
Fig.5  Minimum singular value with all stabilizers at = -0.4 p.u.
Fig.5  Minimum singular value with all stabilizers at = -0.4 p.u.
Fig.5  Minimum singular value with all stabilizers at = -0.4 p.u.
Fig.5  Minimum singular value with all stabilizers at = -0.4 p.u.
Fig.5  Minimum singular value with all stabilizers at = -0.4 p.u.
Fig.6  Minimum singular value with all stabilizers at = 0.0 p.u.
Fig.6  Minimum singular value with all stabilizers at = 0.0 p.u.
Fig.6  Minimum singular value with all stabilizers at = 0.0 p.u.
Fig.6  Minimum singular value with all stabilizers at = 0.0 p.u.
Fig.6  Minimum singular value with all stabilizers at = 0.0 p.u.
Fig.7  Minimum singular value with all stabilizers at = 0.4 p.u.
Fig.7  Minimum singular value with all stabilizers at = 0.4 p.u.
Fig.7  Minimum singular value with all stabilizers at = 0.4 p.u.
Fig.7  Minimum singular value with all stabilizers at = 0.4 p.u.
Fig.7  Minimum singular value with all stabilizers at = 0.4 p.u.
Qe/p.u.Pe/p.u.loading
0.1670.8nominal
0.41.2heavy
0.010.2light
Tab.1  Loading conditions
Fig.8  Profiles of objective function
Fig.8  Profiles of objective function
Fig.8  Profiles of objective function
Fig.8  Profiles of objective function
Fig.8  Profiles of objective function
controller parameterscoordinated designcoordinated designcoordinated design
CPSSUPFCdual-input PSSUPFCPSS2BUPFC
ω input P input
G1007.14400.26900.1505–17.52122.00698.4627
T10.63240.27850.06460.81470.051.49400.4854
T21.00730.81830.050.90581.05680.15760.8003
T31.36390.54690.95750.12700.96490.97060.1419
T40.9751.09240.050.91340.90540.95720.4446
Tab.2  Optimal parameters and settings of the proposed controllers
nominalheavylight
eigenvaluedamping ratioeigenvaluedamping ratioeigenvaluedamping ratio
without PSS, dual-input PSS and UPFC0.0773±i6.56–0.179±i0.66–0.01180.26090.0775±i6.37–0.311±i0.82–0.01220.35460.0713±i6.5243–0.0109
CPSS & UPFC–2±i2.65–1.87±i2.13–1.77±i1.370.60190.65960.7922–2.74±i4.06–1.5±i0.84–1.18±i0.53–1.07±i0.360.55930.87150.91150.9477–1.99±i5.73–1.59±i1.10.32770.8223
dual-input PSS & UPFC–1.264±i5.25–6.6±i1.55–0.95±i0.110.92340.97360.9936–9.45±i6.54–3.15±i1.70–11.93±i3.41–0.95±i0.110.82210.88040.96140.9936–5.35±i5.62–4.63±i3.05–0.79±i0.490.68960.83550.8512
PSS2B & UPFC–12.64±5.25i–6.82±1.38i–0.95-0.11i–5.13±0.25i0.92350.98020.99380.9988–10.30±5.72i–7.77±3.05i–0.95±0.11i0.87410.93100.9937–2.98±2.98i–8.68±6.43i–12.85±4.51i0.70730.80360.9435
Tab.3  Eigenvalues and damping ratios of power system before and after the coordinated tuning with
Fig.9  Nonlinear simulation of test system
Fig.9  Nonlinear simulation of test system
Fig.9  Nonlinear simulation of test system
Fig.9  Nonlinear simulation of test system
Fig.9  Nonlinear simulation of test system
Fig.10  Dynamic responses for speed deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.10  Dynamic responses for speed deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.10  Dynamic responses for speed deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.10  Dynamic responses for speed deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.10  Dynamic responses for speed deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.11  Dynamic responses for active power deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.11  Dynamic responses for active power deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.11  Dynamic responses for active power deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.11  Dynamic responses for active power deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
Fig.11  Dynamic responses for active power deviation at (a) nominal, (b) heavy, and (c) light loading conditions. Solid line: PSS2B & UPFC, dashed line: dual-input PSS & UPFC, dotted line: CPSS & UPFC
1 Kundur P, Balu N J, Lauby M G. Power System Stability and Control. New York: McGraw-Hill, 1994
2 Rogers G. Power System Oscillations. Boston: Kluwer Academic, 2000
3 Kitauchi Y, Taniguchi H, Shirasaki T, Ichikawa Y, Amano M, Banjo M. Experimental verification of multi-input PSS with reactive power input for damping low frequency power swing. IEEE Transactions on Energy Conversion , 1999, 14(4): 1124-1130
doi: 10.1109/60.815037
4 Kamwa I, Grondin R, Trudel G. IEEE PSS2B versus PSS4B: The limits of performance of modern power system stabilizers. IEEE Transactions on Power Systems , 2005, 20(2): 903-915
doi: 10.1109/TPWRS.2005.846197
5 Liu Y, Li J, Li C. Robust excitation control of multi-machine multi-load power systems using Hamiltonian function method. Frontiers of Electrical and Electronic Engineering in China , 2011, 6(4): 547-555
doi: 10.1007/s11460-011-0183-6
6 IEEE Power Engineering Society. IEEE Recommended Practice for Excitation System Models for Power System Stability Studies (IEEE Std 421.5-2005). 2006
7 Shakarami M R, Kazemi A. Robust design of static synchronous series compensator-based stabilizer for damping inter-area oscillations using quadratic mathematical programming. Journal of Zhejiang University-Science C , 2010, 11(4): 296-306
doi: 10.1631/jzus.C0910428
8 Chang J, Chow J H. Time-optimal series capacitor control for damping interarea modes in interconnected power systems. IEEE Transactions on Power Systems , 1997, 12(1): 215-221
doi: 10.1109/59.574942
9 Abido M A. Genetic-based TCSC damping controller design for power system stability enhancement. In: Proceedings of International Conference on Electric Power Engineering . 1999, 165
10 Abido M. Pole placement technique for PSS and TCSC-based stabilizer design using simulated annealing. International Journal of Electrical Power & Energy Systems , 2000, 22(8): 543-554
doi: 10.1016/S0142-0615(00)00027-2
11 Rezazadeh A, Sedighizadeh M, Hasaninia A.Coordination of PSS and TCSC controller using modified particle swarm optimization algorithm to improve power system dynamic performance. Journal of Zhejiang University-Science C , 2010, 11(8): 645-653
12 Baker R, Guth G, Egli W, Eglin P. Control algorithm for a static phase shifting transformer to enhance transient and dynamic stability of large power systems. IEEE Transactions on Power Apparatus and Systems , 1982, PAS-101(9): 3532-3542
doi: 10.1109/TPAS.1982.317580
13 Jiang F, Choi S, Shrestha G. Power system stability enhancement using static phase shifter. IEEE Transactions on Power Systems , 1997, 12(1): 207-214
doi: 10.1109/59.574941
14 Jiang T, Chen C, Cao G. Nonlinear optimal predictive controller for static var compensator to improve power system damping and to maintain voltage. Frontiers of Electrical and Electronic Engineering in China , 2006, 1(4): 380-384
doi: 10.1007/s11460-006-0073-5
15 Sun L Y, Tong S, Liu Y. Adaptive backstepping sliding mode H control of static var compensator. IEEE Transactions on Control Systems Technology , 2011, 19(5): 1178-1185
doi: 10.1109/TCST.2010.2066975
16 Rao P S, Sen I. A QFT based robust SVC controller for improving the dynamic stability of power systems. In: Proceedings of the Fourth International Conference on Advances in Power System Control, Operation and Management . 1997, 1: 366-370
17 Parniani M, Iravani M. Optimal robust control design of static VAR compensators. IEE Proceedings-Generation, Transmission and Distribution , 1998, 145(3): 301-307
18 Jalilvand A, Safari A. Design of an immune-genetic algorithm-based optimal state feedback controller as UPFC. In: Proceedings of the 6th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology . 2009, 36-39
19 Dash P, Mishra S, Panda G. Damping multimodal power system oscillation using a hybrid fuzzy controller for series connected FACTS devices. IEEE Transactions on Power Systems , 2000, 15(4): 1360-1366
doi: 10.1109/59.898113
20 Dong L, Zhang L, Crow M. A new control strategy for the unified power flow controller. In: Proceedings of the IEEE Power Engineering Society Winter Meeting . 2002, 1: 562-566
21 Schoder K, Hasanovic A, Feliachi A. Fuzzy damping controller for the unified power flow controller. In: Proceedings of the IEEE Power Engineering Society Winter Meeting 2000, 5-21
22 Nguyen T, Gianto R. Neural networks for adaptive control coordination of PSSs and FACTS devices in multimachine power system. IET Generation, Transmission & Distribution , 2008, 2(3): 355-372
doi: 10.1049/iet-gtd:20070125
23 Lei X, Lerch E N, Povh D. Optimization and coordination of damping controls for improving system dynamic performance. IEEE Transactions on Power Systems , 2001, 16(3): 473-480
doi: 10.1109/59.932284
24 Cai L J, Erlich I. Simultaneous coordinated tuning of PSS and FACTS damping controllers in large power systems. IEEE Transactions on Power Systems , 2005, 20(1): 294-300
doi: 10.1109/TPWRS.2004.841177
25 Pourbeik P, Gibbard M J. Simultaneous coordination of power system stabilizers and FACTS device stabilizers in a multimachine power system for enhancing dynamic performance. IEEE Transactions on Power Systems , 1998, 13(2): 473-479
doi: 10.1109/59.667371
26 Wang H. Damping function of unified power flow controller. IEE Proceedings-Generation, Transmission and Distribution , 1999, 146(1): 81-87
27 Yoshimura K, Uchida N. Multi input PSS optimization method for practical use by considering several operating conditions. In: Proceedings of the IEEE Power Engineering Society Winter Meeting . 1999, 749-754
28 Hashemi Y, Kazemzadeh R, Azizian M R, Sadeghi A, Morsali J. Simultaneous coordinated tuning of UPFC and multi-input PSS for damping of power system oscillations. In: Proceedings of the 26th International Power System Conference . 2011
29 Alves da Silva A, Abr?o P J. Applications of evolutionary computation in electric power systems. In: Proceedings of the Congress on Evolutionary Computation . 2002, 1057-1062
30 Abdel-Magid Y, Abido M. Optimal multiobjective design of robust power system stabilizers using genetic algorithms. IEEE Transactions on Power Systems , 2003, 18(3): 1125-1132
doi: 10.1109/TPWRS.2003.814848
31 Do Bomfim A L B, Taranto G N, Falcao D M. Simultaneous tuning of power system damping controllers using genetic algorithms. IEEE Transactions on Power Systems , 2000, 15(1): 163-169
doi: 10.1109/59.852116
32 Jayabarathi T, Bahl P, Ohri H, Yazdani A, Ramesh V. A hybrid BFA-PSO algorithm for economic dispatch with valve-point effects. Frontiers in Energy , 2012, 6(2): 155-163
33 Alrashidi M, El-Hawary M. A survey of particle swarm optimization applications in power system operations. Electric Power Components and Systems , 2006, 34(12): 1349-1357
doi: 10.1080/15325000600748871
34 del Valle Y, Venayagamoorthy G K, Mohagheghi S, Hernandez J C, Harley R G. Particle swarm optimization: Basic concepts, variants and applications in power systems. IEEE Transactions on Evolutionary Computation , 2008, 12(2): 171-195
doi: 10.1109/TEVC.2007.896686
35 Kennedy J, Eberhart R. Particle swarm optimization. In: Proceedings of International Conference on Neural Networks . 1995, 1942-1948
36 Hamdan A. An investigation of the significance of singular value decomposition in power system dynamics. International Journal of Electrical Power & Energy Systems , 1999, 21(6): 417-424
doi: 10.1016/S0142-0615(99)00011-3
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