Artificial Bee Colony Based Power System Stabilizer Design for a TurboGenerator in a Single-Machine Power System

This paper presents an Artificial Bee Colony (ABC) algorithm for optimal tuning of the Power System Stabilizer (PSS) in a Single-Machine InfiniteBus (SMIB) power system. The design problem of robustly tuning PSS parameters is formulated as an optimization problem according to the time domainbased objective function which is solved by the ABC technique that has strong ability to find the most optimistic results. To ensure performance and robustness of the proposed control strategy to stabilize low frequency oscillations The design process takes a wide range of operating conditions. The effectiveness of the proposed ABC based PSS is demonstrated on a SMIB power system through the nonlinear time domain simulation and some performance indices under different operating conditions in comparison with the particle swarm optimization based tuned stabilizer and conventional PSS. Results evaluation show that the proposed stabilizer achieves good robust performance for wide range of system operation conditions and is superior to the other PSSs. Moreover, the proposed control strategy has simple structure, easy to implement and tune which can be useful for the real world complex power system.

[1]  P. Kundur,et al.  Application of Power System Stabilizers for Enhancement of Overall System Stability , 1989, IEEE Power Engineering Review.

[2]  P. Kundur,et al.  Power system stability and control , 1994 .

[3]  Amin Safari,et al.  Multi-machine power system stabilizers design using chaotic optimization algorithm , 2010 .

[4]  Dervis Karaboga,et al.  A comparative study of Artificial Bee Colony algorithm , 2009, Appl. Math. Comput..

[5]  Yuan-Yih Hsu,et al.  Design of a Proportional-Integral Power System Stabilizer , 1986, IEEE Transactions on Power Systems.

[6]  K. R. Padiyar,et al.  Power system dynamics : stability and control , 1996 .

[7]  Dervis Karaboga,et al.  Artificial bee colony algorithm , 2010, Scholarpedia.

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

[9]  Om P. Malik,et al.  An artificial neural network based adaptive power system stabilizer , 1993 .

[10]  H. Shayeghi,et al.  Multi-stage fuzzy load frequency control using PSO , 2008 .

[11]  Dantong Ouyang,et al.  An artificial bee colony approach for clustering , 2010, Expert Syst. Appl..

[12]  M. J. Gibbard,et al.  Robust design of fixed-parameter power system stabilisers over a wide range of operating conditions , 1991 .

[13]  J. Nanda,et al.  Multi-machine power system stabilizer design by rule based bacteria foraging , 2007 .

[14]  S. N. Omkar,et al.  Applied Soft Computing Artificial Bee Colony (abc) for Multi-objective Design Optimization of Composite Structures , 2022 .

[15]  D. A. Pierre,et al.  A Perspective on Adaptive Control of Power Systems , 1987, IEEE Transactions on Power Systems.

[16]  Miss A.O. Penney.  (b) , 1974, The New Yale Book of Quotations.

[17]  Amin Safari,et al.  A robust PSSs design using PSO in a multi-machine environment , 2010 .

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