Shivakumar RANGASAMY, Panneerselvam MANICKAM

Stability analysis of multimachine thermal power systems using the nature-inspired modified cuckoo search algorithm

The stability of modern interconnected thermal power systems is greatly affected by the presence of low-frequency inertial oscillations in the system, due to various forms of disturbances experienced. This paper provides an efficient damping solution to these oscillations based on nature-inspired modified cuckoo search algorithm-based controller design. The proposed controller design is formulated as a parameter optimization problem based on damping ratio and time-domain error deviations. The effectiveness of the proposed damping controller design is illustrated by performing the nonlinear time domain simulations of the test multimachine power systems under various operating conditions and disturbances. Moreover, an exhaustive comparative stability analysis is performed based on the damping performance of the modified cuckoo search controller design over the genetic algorithm-based and cuckoo search algorithm-based controller designs.

Anahtar Kelimeler:

Low-frequency inertial oscillations, damping ratio, nature-inspired optimization, cuckoo search algorithm, multimachine thermal systems

Stability analysis of multimachine thermal power systems using the nature-inspired modified cuckoo search algorithm

Keywords:

Low-frequency inertial oscillations, damping ratio, nature-inspired optimization, cuckoo search algorithm, multimachine thermal systems,

PDF

___

E.R. Anarmarzi, M.R. Feyzi, M.T. Hagh, “Hierarchical fuzzy controller applied to multiinput power system stabi- lizer”, Turkish Journal of Electrical & Computer Sciences, Vol. 18, pp. 541–552, 2010.
A.D. Falehi, M. Rostami, A. Doroudi, “Optimization and coordination of SVC-based supplementary controllers and PSSs to improve power system stability using a genetic algorithm”, Turkish Journal of Electrical & Computer
Sciences, Vol. 20, pp. 639–654, 2012.
H. Yassami, A. Darabi, S.M.R. Rafiei, “Power system stabilizer design using Pareto multiobjective optimization approach”, Electric Power Systems Research, Vol. 80, pp. 838–846, 2010.
M.J. Gibbard, “Robust design of fixed-parameter power system stabilizers over a wide range of operating conditions”, IEEE Transactions on Power Systems, Vol. 16, pp. 794–800, 1991.
P. Gahinet, P. Apkarian, “A linear matrix inequality approach to H∞ control”, International Journal of Robust and Nonlinear Control, Vol. 4, pp. 421–448, 1994.
M.A. Abido, Y.L.A. Magid, “Adaptive tuning of power system stabilizers using radial basis function networks”, Electric Power Systems Research, Vol. 49, pp. 21–29, 1999.
N. Hosseinzadeh, A. Kalam, “A hierarchical neural network adaptive power system stabilizer”, International Journal of Power and Energy Systems, Vol. 19, pp. 28–33, 1999.
J.A.L. Barreiros, A.M.D. Ferreira, “A neural power system stabilizer trained using local linear controllers in a gain scheduling scheme”, International Journal of Electrical Power and Energy Systems, Vol. 27, pp. 473–479, 2005.
A.L. Elshafei, K.A. El-Metwally, A.A. Shaltout, “A variable structure fuzzy logic stabilizer for single and multima- chine power systems”, Control Engineering Practice, Vol. 13, pp. 413–423, 2005.
M. Abido, “Pole placement technique for PSS and TCSC-based stabilizer design using simulated annealing”, International Journal of Electrical Power and Energy Systems, Vol. 22, pp. 534–554, 2000.
M.A. Abido, Y.L.A. Magid, “Optimal design of PSS using evolutionary programming”, IEEE Transactions on Energy Conversion”, Vol. 17, pp. 429–436, 2002.
H. Shayeghi, A. Safari, H.A. Shayanfar, “Multimachine power system stabilizers design using PSO algorithm”, International Journal of Electrical Power and Energy Systems, Vol. 1, pp. 226–233, 2008.
M. Nayeripour, M.R. Narimani, T. Niknan, “Application of modified shuffled frog leaping algorithm on optimal power flow incorporating unified power flow controller”, International Journal of Modeling and Optimization, Vol. 1, pp. 191–198, 2011.
X.S. Yang, Nature-Inspired Metaheuristic Algorithms, Bristol, UK, Luniver Press, 2008.
P. Civicioglu, “Transforming geocentric Cartesian coordinates to geodetic coordinates by using differential search algorithm”, Computers & Geosciences, Vol. 46, pp. 229–247, 2012.
B. Pal, B. Chaudhuri, Robust Control in Power Systems, New York, NY, USA, Springer Science, 2005.
M.A. Pai, Energy Function Analysis for Power System Stability, Norwell, MA, USA, Kluwer Academic Publishers, 1989. [18] J. Machowski, J. Bialek, J.R Bumby, Power System Dynamics: Stability and Control, Chichester, UK, Wiley, 2008. [19]X.S. Yang, S. Deb, “Cuckoo search via levy flights”, Proceedings of the World Congress on Nature and Biologically Inspired Computing, pp. 210–214, 2009.
X.S. Yang, S. Deb, “Engineering optimization by cuckoo search”, International Journal of Mathematical Modelling and Numerical Optimization, Vol. 1, pp. 330–343, 2010.
E. Valian, S. Mohanna, S. Tavokoli, “Improved cuckoo search algorithm for global optimization”, International Journal of Communications and Information Technology, Vol. 1, pp. 31–44, 2011.
X.S. Yang, Engineering Optimization: An Introduction with Metaheuristic Applications, Chichester, UK, Wiley, 2010. Y.L.A. Magid, M.A. Abido, “Optimal multiobjective design of robust power system stabilizers using genetic algorithms”, IEEE Transactions on Power Systems, Vol. 18, pp. 1125–1131, 2003.
S. Panda, C. Ardil, “Real coded genetic algorithm for robust power system stabilizer design”, International Journal of Electrical, Computer and System Engineering, Vol. 2, pp. 6–14, 2008.
Z. Wang, C.Y. Chung, K.P. Wong, D. Gan, Y. Xue, “Probabilistic power system stabilizer design with consideration of optimal siting using recursive genetic algorithm”, European Transactions on Electrical Power, Vol. 21, pp. 1409– 1424, 2011.
M.A. Abido, “Parameter optimization of multimachine power system stabilizers using genetic local search”, Elec- trical Power and Energy Systems, Vol. 23, pp. 785–794, 2001.