On-time stabilization of single-machine power system connected to infinite bus by using optimized fuzzy-PID controller

Power systems are subjected to disturbance that may cause unacceptable power oscillations in transmission lines. The use of power system stabilizer has a great effect in controlling and damping of these low-frequency oscillations. Study and discussion in the field of designing different kinds of stabilizers constitutes one of the dynamic research areas concerning power systems. The major problem of stabilizers lies in their failure to respond well in different work conditions. To solve this problem, the fuzzy controller has been used. The aim of this study is to design Fuzzy-PID stabilizer in single-machine system connected to infinite bus by using hybrid big bang big crunch algorithm. The system was tested under different conditions, by changing the load by %+25 and %-25. Simulation results are compared in three scenarios and by applying three-phase to ground fault for the duration of 70ms. The results revealed good efficiency of this controller in stabilizing of power system in different conditions.

[1]  Charles V. Camp DESIGN OF SPACE TRUSSES USING BIG BANG–BIG CRUNCH OPTIMIZATION , 2007 .

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

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

[4]  Hisham M. Soliman,et al.  PSO-BASED POWER SYSTEM STABILIZER FOR MINIMAL OVERSHOOT AND CONTROL CONSTRAINTS , 2008 .

[5]  Deqiang Gan,et al.  Probabilistic power system stabilizer design with consideration of optimal siting using recursive Genetic Algorithm , 2011 .

[6]  R.A. Ramos,et al.  Design and application fuzzy PSS for power systems subject to random abrupt variations of the load , 2004, Proceedings of the 2004 American Control Conference.

[7]  Mostafa Sedighizadeh,et al.  An Efficient Hybrid Big Bang–Big Crunch Algorithm for Multi-objective Reconfiguration of Balanced and Unbalanced Distribution Systems in Fuzzy Framework , 2013 .

[8]  Shaoru Zhang,et al.  An Improved Simple Adaptive Control Applied to Power System Stabilizer , 2009 .

[9]  Ibrahim Eksin,et al.  A new optimization method: Big Bang-Big Crunch , 2006, Adv. Eng. Softw..

[10]  Bo Liu,et al.  Improved particle swarm optimization combined with chaos , 2005 .

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

[12]  R.C. Schaefer,et al.  Understanding Power-System Stability , 2005, IEEE Transactions on Industry Applications.

[13]  A. Dysko,et al.  Enhanced Power System Stability by Coordinated PSS Design , 2010, IEEE Transactions on Power Systems.

[14]  A. M. El-Zonkoly,et al.  Optimal tunning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization , 2009, Expert Syst. Appl..

[15]  Herbert Werner,et al.  Robust tuning of power system stabilizers using LMI-techniques , 2003, IEEE Trans. Control. Syst. Technol..

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

[17]  M. A. Abido,et al.  A novel approach to conventional power system stabilizer design using tabu search , 1999 .

[18]  H. Shayanfar,et al.  LFC DESIGN USING HBMO TECHNIQUE IN INTERCONNECTED POWER SYSTEM , 2011 .

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