Design of state feedback stabilizer for multi machine power system using PSO algorithm

In this paper an optimal state feedback design as a power system stabilizer (PSS) using particle swarm optimization (PSO) is presented. The problem of selecting the parameters of the state feedback PSS for a multi machine power system is converted to an optimization problem solved by PSO with the eigenvalue-based objective functions. Both the relative stability of low-frequency modes and the practical implementation of PSSs as Considerations for a stable system are included in the constraints. The locally measured states are fed back at the AVR reference input of each machine after multiplication by suitable feedback gains. The obtained stabilizer is confirmed by eigenvalue analysis and simulation results of a multi machine power system under different operating conditions and exposed to small disturbances.

[1]  Chun-Lung Chen,et al.  Unit commitment with probabilistic reserve: An IPSO approach , 2007 .

[2]  Ross Baldick,et al.  Unit commitment with probabilistic reserve , 2002, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309).

[3]  Daizhan Cheng,et al.  Nonlinear decentralized controller design for multimachine power systems using Hamiltonian function method , 2002, Autom..

[4]  Z. Barton Robust control in a multimachine power system using adaptive neuro-fuzzy stabilisers , 2004 .

[5]  Pedro J. Zufiria,et al.  Design and comparison of adaptive power system stabilizers based on neural fuzzy networks and genetic algorithms , 2007, Neurocomputing.

[6]  A. H. Coonick,et al.  Coordinated synthesis of PSS parameters in multi-machine power systems using the method of inequalities applied to genetic algorithms , 2000 .

[7]  Zhao Hui,et al.  Optimal Design of Power System Stabilizer Using Particle Swarm Optimization , 2006 .

[8]  M. A. Abido,et al.  Optimal Design of Power System Stabilizers Using Evolutionary Programming , 2002, IEEE Power Engineering Review.

[9]  S. Lee Optimal decentralised design for output-feedback power system stabilisers , 2005 .

[10]  R. You,et al.  An on-line adaptive neuro-fuzzy power system stabilizer for multimachine systems , 2003, 2003 IEEE Power Engineering Society General Meeting (IEEE Cat. No.03CH37491).

[11]  M. A. Abido,et al.  Simultaneous stabilization of multimachine power systems via genetic algorithms , 1999, IEEE Transactions on Power Systems.

[12]  M. A. Abido,et al.  Hybridizing rule-based power system stabilizers with genetic algorithms , 1999 .

[13]  Hardiansyah,et al.  A robust H ¿ power system stabilizer design using reduced-order models , 2006 .

[14]  Joe H. Chow,et al.  A comparison of classical, robust, and decentralized control designs for multiple power system stabilizers , 2000 .

[15]  Om P. Malik,et al.  An adaptive power system stabilizer based on the self-optimizing pole shifting control strategy , 1993 .

[16]  A. K. David,et al.  Probabilistic eigenvalue sensitivity analysis and PSS design in multimachine systems , 2003 .

[17]  James Kennedy,et al.  The particle swarm: social adaptation of knowledge , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[18]  M. A. Abido Optimal des'ign of Power System Stabilizers Using Particle Swarm Opt'imization , 2002, IEEE Power Engineering Review.

[19]  M. A. Abido,et al.  Robust design of multimachine power system stabilizers using simulated annealing , 2000 .

[20]  Mohammad Ali Abido,et al.  Robust tuning of power system stabilizers in multimachine power systems , 2000 .

[21]  Haozhong Cheng,et al.  Optimal reactive power flow incorporating static voltage stability based on multi-objective adaptive immune algorithm , 2008 .

[22]  R. You,et al.  An Online Adaptive Neuro-Fuzzy Power System Stabilizer for Multimachine Systems , 2002, IEEE Power Engineering Review.

[23]  M. L. Kothari,et al.  A self-tuning power system stabilizer based on artificial neural network , 2004 .

[24]  Sakti Prasad Ghoshal,et al.  Comparison of intelligent fuzzy based AGC coordinated PID controlled and PSS controlled AVR system , 2007 .

[25]  He Ping,et al.  Studies of the improvement of probabilistic PSSs by using the single neuron model , 2007 .

[26]  M. A. Abido,et al.  Optimal multiobjective design of robust power system stabilizers using genetic algorithms , 2003 .

[27]  K. A. El-Metwally,et al.  A variable-structure adaptive fuzzy-logic stabilizer for single and multi-machine power systems , 2004 .

[28]  H. H. Happ,et al.  Power System Control and Stability , 1979, IEEE Transactions on Systems, Man, and Cybernetics.

[29]  O.P. Malik,et al.  Generalized neuron-based adaptive PSS for multimachine environment , 2005, IEEE Transactions on Power Systems.

[30]  I. Sen,et al.  Robust pole placement stabilizer design using linear matrix inequalities , 2000 .