COORDINATED TUNING OF PID-BASED PSS AND AVR USING BACTERIAL FORAGING-PSOTVAC-DE ALGORITHM

Ida B.G. Manuaba, Muhammad Abdillah, Ardyono Priyadi, and Mauridhi H. Purnomo

References

  1. [1] A. Oonsivilai, B and Marungsri, Stability enhancement for multi-machine power system by optimal PID tuning of power system stabilizer using particle swarm optimization, WSEAS Transactions on Power Systems, 3, 2008, 465–474.
  2. [2] H. Shayeghi, A. Safari, and H.A. Shayanfar, Multimachine power system stabilizers design using PSO algorithm, International Journal of Electrical Power and Energy Systems Engineering, 2008, 226–233.
  3. [3] A.M. El-Zonkoly, Optimal tuning of power systems stabilizer and AVR gains using particle swarm optimization, Elsevier Expert Systems with Applications, 31, 2006, 551–557.
  4. [4] L. Jasa, A. Priyadi, and M.H. Purnomo, PID control formicro-hydro power plants based on neural network, Proceedings of the IASTED Asian Conference: Modelling, Identification and Control (AsiaMIC 2012); Advance in Computer Science and Engineering, Phuket, Thailand, 2012, doi:10.2316/P.2012.769-039.
  5. [5] S.H. Hosseini, R. Rahnavard, and H. Kharrati, Application of genetic algorithm to design PID controller for power system stabilization, http://citeseerx.ist.psu.edu/ (accessed 2009).
  6. [6] M. Soliman, A.-L. Elshafei, F. Bendary, and W. Mansour,Design of a robust fuzzy power system stabilizer, Control and Intelligent Systems, 37, 2009, 227–234.
  7. [7] W.M. Korani, H.T. Dorrah, and H.M. Emara, Bacterial foraging oriented by particle swarm optimization strategy for PID tuning, IEEE International Symposium on ComputationIntelligence in Robotic and Automation (CIRA), 2009, 445–450.
  8. [8] K.T. Chaturvedi, M. Pandit, and L. Srivastava, Particle swarm optimization with time varying acceleration coefficients for non-convex economic power dispatch, Elsevier Electrical Power and Energy Systems, 2009.
  9. [9] S. Mishra, A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation, IEEE Transactions on Evolutionary Computation, 9, 2005, 61–73.
  10. [10] N. Sinha, L.L. Lai, and V.G. Rao, GA optimized PID controllers for automatic generation control of two area reheat thermal systems under deregulated environment, DRPT 2008. Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, Nanjing, China, 2008, 1186–1191.
  11. [11] M. Sedraoui, S. Gherbi, and S. Abdelmalek, A robust controller based on fractional tructure for MIMO plant with multiple delays, Control and Intelligent Systems, 40(2), 2012, 83–94.
  12. [12] I.B.G. Manuaba, R.S. Hartati, A. Soeprijanto, and M.H.Purnomo, The application of particle swarm optimizationeethod to solve economic dispatch problem in electric powersystem bali, The 11th Seminar on Intelligent Technology andIts Applications, Surabaya, Indonesia, October 2010, vol. 11, 461–465.
  13. [13] I.B.G. Manuaba, M. Abdillah, A. Soeprijanto, and M.H.Purnomo, Coordination of PID based power system stabilizerand AVR using combination bacterial foraging technique: Particle swarm optimization, The Fourth International Conference on Modeling, Simulation and Applied Optimization (ICMSAO 2011), Kuala Lumpur, Malaysia, April 2011, 508–514.
  14. [14] B. Selvabala and D. Devaraj, Co-ordinated tuning of AVR-PSS using differential evolution algorithm, IPEC 2010 Conference Proceedings, Sapporo, Japan, 2010, 439–444.
  15. [15] P. Praveena, K. Vaisakh, and S. Rama Mohana Rao, A bacterial foraging PSO-DE algorithm for solving dynamic economic dispatch problem with security constraints, The 2010 Joint International Conference on Power Electronic, Drives and Energy Systems (PEDES) & 2010 Power India, India, 2010, 1–7.

Important Links:

Go Back