Coordinated AVR-PSS for Transient Stability Using Modified Particle Swarm Optimization
DOI:
https://doi.org/10.11113/jt.v67.2758Keywords:
AVR, coordinated design, IPSO, power system stability, PSS, transient stabilityAbstract
This paper presents the coordination between the Automatic Voltage Regulator (AVR) and Power System Stabilizers (PSS) to increase the system damping over a wide range of systems’ operating conditions in order to improve the transient stability performance and steady state performance of the system. The coordinated design problem is formulated as an optimization problem which is solved using Iteration Particle Swarm Optimization (IPSO). The application of IPSO technique is proposed to optimize the parameters of the AVR and PSS to minimize the oscillations in power system during disturbances in a single machine infinite bus system (SMIB). The performance of the proposed IPSO technique is compared with the traditional PSO technique. The comparison considered is in terms of parameter accuracy and computational time. The results of the time domain simulations and eigenvalue analysis show that the proposed IPSO method provides a better optimization technique as compared to the traditional PSO technique. Â
References
A. M., El-Zonkoly. 2006. Optimal Tuning of Power Systems Stabilizers and AVR Gains Using Particle Swarm Optimization. Expert Systems with Applications. 31(3): 551–557.
K. Hirayama, Y. T., K. Takagi, H. Murakami, M. Shibata, H. Nagamura, Y. Takagi. 1993. Digital AVR Application to Power Plants. IEEE Transactions on Energy Conversion. 8(4): 602–609.
A. Dysko, W. E. L., J. O'Reilly. 2010. Enhanced Power System Stability by Coordinated PSS Design. IEEE Transactions on Power Systems. 25(1): 413–422.
A. Mahabuba, and M. A. Khan. 2009. Small Signal Stability Enhancement of a Multi-machine Power System Using Robust and Adaptive Fuzzy Neural Network-Based Power System Stabilizer. European Transactions on Electrical Power. 19(7): 978–1001.
S. Mishra. 2006. Neural-network-based Adaptive UPFC for Improving Transient Stability Performance of Power System. IEEE Transactions on Neural Networks. 17(2): 461–470.
K. Sundareswaran, and S. Razia Begum. 2004. Genetic Tuning of a Power System Stabilizer. European Transactions on Electrical Power. 14(3): 151–160.
D. Sumina, N. Bulić, and M. Mišković. 2011. Parameter Tuning of Power System Stabilizer Using Eigenvalue Sensitivity. Electric Power Systems Research. 81(12): 2171–2177.
P. Kundur. 1994. Power System Stability and Control. McGraw-Hill.
M. A. Furini, A. L. S. Pereira, and P. B. Araujo. 2011. Pole Placement by Coordinated Tuning of Power System Stabilizers and FACTS-POD Stabilizers. International Journal of Electrical Power and Energy Systems. 33(3): 615–622.
G. Gurrala and I. Sen. 2010. Power System Stabilizers Design for Interconnected Power Systems. IEEE Transactions on Power Systems. 25(2).
M. Ramirez-Gonzalez, and O. P. Malik. 2008. Power System Stabilizer Design Using an Online Adaptive Neurofuzzy Controller With Adaptive Input Link Weights. IEEE Transactions on Energy Conversion. 23(3): 914–922.
D. P. Ke, C. Y. C., Yusheng Xue. 2011. An Eigenstructure-Based Performance Index and Its Application to Control Design for Damping Inter-Area Oscillations in Power Systems. IEEE Transactions on Power Systems. 26(4).
M. A. Abido, and Y. L. Abdel-Magid. 2000. Robust Design of Multimachine Power System Stabilisers Using Tabu Search Algorithm. Generation. Transmission and Distribution, IEE Proceedings. 147(6): 387–394.
S. S. S. Farahani, M. N., M. G. Naraghi, M. B. Tabar, A. Javadian. 2011. Power System Stabilizer Parameters Tuning Based on Tabu Search in a Multi Machine Power System. Australian Journal of Basic and Applied Sciences. 5(8): 624–630.
M. M. Pedram, and H. Seifi. 1997. Extended Algorithm of a Fuzzy-set Based Power-system Stabilizer with Genetic Algorithm Timing. European Transactions on Electrical Power. 7(3): 205–210.
S. S. Shamsabad Farahani, M. N. Mohammad Bigdeli Tabar, and A. J. Mehdi Ghasemi Naraghi. 2011. Multi-machine Power System Stabilizer Adjustment using Simulated Annealing. Indian Journal of Science and Technology. 4(8): 886–889.
G. Naresh, M. R. R., K.Ravindra, S. V. L. Narasimham. 2011. Optimal Design of Multi-Machine Power System Stabilizer Using Genetic Algorithm, Innovative Systems Design and Engineering. 2(4).
Z. Wang, C. Y. Chung, K. P. Wong. 2011. Probabilistic Power System Stabilizer Design with Consideration of Optimal Siting Using Recursive Genetic Algorithm. European Transactions on Electrical Power. 21(3): 1409–1424.
A. Jalilvand, R. A., E. Khalkhali. 2011. Optimal Design of PID Power System Stabilizer in Multi-Machine Power System using PSO and Genetic Algorithm. International Review of Electrical Engineering. 6(2): 907–912.
N. C. Pahalawaththa, G. S. Hope, and O. P. Malik. 1991. Multivariable Self-tuning Power System Stabilizer Simulation and Implementation Studies. IEEE Transactions on Energy Conversion. 6(2): 310–319.
K. R. Padiyar. 2008. Power System Dynamics Stability and Control. Second Edition. ed. BS Publications, Giriraj Lane, Sultan Bazar, Hyderabad - 500 095 - AP.
A. D. Falehi, M. R., H. Mehrjardi. 2011. Transient Stability Analysis of Power System by Coordi-nated PSS-AVR Design Based on PSO Technique. Engineering. 3(5): 478–484.
J. M. Kim, and S. I. Moon. 2006. A Study on a New AVR Parameter Tuning Concept Using On-line Measured Data with the Real-time Simulator. European Transactions on Electrical Power. 16(3): 235–246.
E. Hossam, M. A Mostafa,.E. S. Adel, A. Emary, Kamel Yassin. 2011. Design and Allocation of Power System Stabilizers Using the Particle Swarm Optimization Technique for an Interconnected Power System. Int J Electrical Power and Energy Systems. doi:10.1016/j.ijepes. 2011 .09.005.
Y. Abdel-Magid, M. Abido, and A. Mantaway. 2000. Robust Tuning of Power System Stabilizers In Multimachine Power Systems. IEEE Transactions on Power Systems. 15(2): 735–740.
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