Indian Journal of Science and Technology

Open Access Open Access  Restricted Access Subscription Access

Multi-Machine Power System Stabilizer Adjustment Using Simulated Annealing


Affiliations
1 Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran, Islamic Republic of
 

In this paper, the authors are willing to find the optimal and robust design for power system stabilizers (PSSs) in a multi-machine power system. In this regard a new Meta heuristic method as Simulated Annealing (SA) is used. The PSS parameters are computed to assure maximum damping performance under different scenarios. A multi machine electric power system is used to illustrative the performance of proposed method. The efficacy of this technique in damping local and inter-area modes of oscillations in multimachine power systems is confirmed through nonlinear simulation results. Simulation results are carried out by numerical simulations on MATLAB software.

Keywords

Multi Machine, Power System Stabilizer, Low Frequency Oscillations, Simulated Annealing
User

  • deMello FP and Concordia C (1996) Concepts of synchronous machine stability as affected by excitation control. IEEE Trans. Power Appar. Syst. 88, 316–329.

  • Kundur P (1994) Power System Stability and Control. McGraw-Hill Press.

  • Larsen E and Swann D (1981) Applying power system stabilizers. IEEE Trans. Power Appar. Syst. PAS-100, 3017–3046.

  • Abdel-Magid YL, Abido MA, Al-Baiyat S and Mantawy AH (1999) Simultaneous stabilization of multimachine power systems via genetic algorithms. IEEE Trans. Power Syst. 14, 1428–1439.

  • Chatterje S, Ghoshal P and Mukherjee V (2011) Chaotic ant swarm optimization for fuzzy-based tuning of power system stabilizer. Intl. J. Electrical Power & Energy Systems, 33(3), 657-672.

  • El-Zonkoly AM, Khalil AA and Ahmied NM (2009) Optimal tuning of lead-lag and fuzzy logic power system stabilizers using particle swarm optimization. Expert Systems with Appl. 36, 2097–2106.

  • Ghoshal SP, Chatterjee A and Mukherjee V (2009) Bioinspired fuzzy logic based tuning of power system stabilizer. Expert Systems with Appl. 36(5), 9281-9292.

  • Chaturvedi DK and Malik OP (2008) Neurofuzzy Power System Stabilizer. IEEE Transactions on Energy Conversion. 23(3), 887-896.

  • Talaat EA, Abdennour A and Al-Sulaiman AA (2010) Design and experimental investigation of a decentralized GA-optimized neuro-fuzzy power system stabilizer. Intl. J. of Electrical Power & Energy Systems. 32(7), 751-759.

  • Soliman M, Elshafei AL, Bendary F and Mansour F (2010) W. Robust decentralized PID-based power system stabilizer design using an ILMI approach. Electric Power Systems Res. 80(12), 1488-1497.

  • Rigatos G and Siano P (2010) Design of robust electric power system stabilizers using Kharitonov’s theorem. Mathematics & Computers in Simulation, doi:10.1016/j.matcom.2010.07.008.

  • Hussein T, Saad MS, Elshafei AL and Bahgat A (2010) Damping inter-area modes of oscillation using an adaptive fuzzy power system stabilizer. Electric Power Systems Res. 80(12), 1428-1436.

  • Hussein T, Saad MS, Elshafei AL and Bahgat A (2009) Robust adaptive fuzzy logic power system stabilizer. Expert Systems with Appl. 36(10), 12104-12112.

  • Shayeghi H, Shayanfar HA, Safari A and Aghmasheh RA (2010a) Robust PSSs design using PSO in a multimachine environment. Energy Conversion & Management. 51, 696–702.

  • Shayeghi H, Shayanfar HA, Jalilzadeh S and Safari A (2010b) Multi-machine power system stabilizers design using chaotic optimization algorithm. Energy Conversion & Management. 51, 1572–1580.

  • Yassami H, Darabi A and Rafiei SMR (2010) Power system stabilizer design using Strength Pareto multiobjective optimization approach. Electric Power Systems Res. 80, 838–846.

  • Wanga SK, Chiou JP and Liu CW (2009) A parameters tuning of power system stabilizers using improved ant direction hybrid differential evolution. Electrical Power and Energy Systems. 31, 34–42.

  • Sauer PW and Pai MA (1997) Power system dynamics and stability. Prentice Hall. Chapter 7, pp: 193-260.

  • Randy LH and Sue EH (2004) Practical Genetic Algorithms. Second Edition. John Wiley & Sons, pp: 51- 65.


Abstract Views: 575

PDF Views: 82




  • Multi-Machine Power System Stabilizer Adjustment Using Simulated Annealing

Abstract Views: 575  |  PDF Views: 82

Authors

Shoorangiz Shams Shamsabad Farahani
Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran, Islamic Republic of
Mehdi Nikzad
Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran, Islamic Republic of
Mohammad Bigdeli Tabar
Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran, Islamic Republic of
Mehdi Ghasemi Naraghi
Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran, Islamic Republic of
Ali Javadian
Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran, Islamic Republic of

Abstract


In this paper, the authors are willing to find the optimal and robust design for power system stabilizers (PSSs) in a multi-machine power system. In this regard a new Meta heuristic method as Simulated Annealing (SA) is used. The PSS parameters are computed to assure maximum damping performance under different scenarios. A multi machine electric power system is used to illustrative the performance of proposed method. The efficacy of this technique in damping local and inter-area modes of oscillations in multimachine power systems is confirmed through nonlinear simulation results. Simulation results are carried out by numerical simulations on MATLAB software.

Keywords


Multi Machine, Power System Stabilizer, Low Frequency Oscillations, Simulated Annealing

References





DOI: https://doi.org/10.17485/ijst%2F2011%2Fv4i8%2F30888