Transient Stability Optimization based on increasing the Critical Clearing Time using Particle Swarm Optimization

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Transient stability Analysis under fault condition is one of the most important concept for a secure and reliable power system operation. Any delay time to cleared the fault and remove the line may be caused the system unstable. Increasing the clearing timetc leads to increase the rotor angle of the generator and go towards the instability system. The clearing time before the system become unstable is called the critical clearing time tcc. This article design a new architecture algorithm to improve the transient stability of the system under fault condition by increase the critical clearing time without adding any external dives. An artificial intelligence technique of Particle Swarm Optimization PSO has been used for this purpose. PSO technique minimize the maximum rotor angle of the generator according to optimize the control variable of the system such as the magnitude voltage of the generator. A load flow analysis based on Newton Raphson method has been used for the pre fault calculation. The two state equations for both during and post fault cases are solved using the modified Euler method to calculate the rotor angle of the generators. Different cases of clearing time are tested in this article to specified the system stability and access to the critical clearing time. The propose algorithm has been applied on the IEEE 9 bus system. This algorithm improve the system transient stability by increasing the critical clearing time by 28%. The propose algorithm are programming by author using matlab software.

     

     


  • Keywords


    Transient Stability Analysis, Fault condition, rotor swing angle, critical clearing time, Particle Swarm Optimization.

  • References


      [1] D P Kothari and I J Nagrath, “Modern Power System Analysis, Fourth edition, McGraw Hill Education”, 2013.

      [2] Mohammad Abdul Baseer, “ Transient Stability Improvement of Multi-machine Power System using Fuzzy Controlled TCSC,” JOSR Journal of Electrical and Electronics Engineering, Vol. 9, Isuue 1, Ver 1, January, 2014, pp. 28-40.

      [3] Rampreet Manjhi & Ramjee Prasad Gupta, “Transient Stability Analysis of the IEEE 9 Bus Multimachine System using the Electrical Transient Analyzer Program(ETAP)Software, ” International Journal of Electrical and Electronics Engineering (IJEEE), Vol. 5, Issue 3, May 2016.

      [4] Ramlas Das, D. K. Tanti, “Transient Stability of 11- bus system using SVC and improvement of voltage profiel in transmission line using seroiuse compensator,” American Journal of Electrical Power and Energy System, 3(4), August, 2014, pp. 76-85.

      [5] Bablesh Kumar Jha, Ramjee Prasad Gupta, Upendra,“Combined Operation of SVC, PSS and Incresing Enertia of Machine for Power System Transient Stability Enhancement,” International Jounal of Applied Power Engineering,” Vol. 3, No. 1, April 2014, pp.15-22.

      [6] Ramesh Kumari, Parveen Kumar, “Improvement in Rotor Stability in 3 Mchine 9 Bus System Using TCSC, SVC, SSSC,” International Jounal of Advanced in Electrical. Electronics and Instrumenttation Engineering, ” Vol. 5, Issue 8, August 2016.

      [7] G V chiranjeevi Adari, “Transient Stability Improvement of Single Machine Infinite Bus (SMIB) System using Distributed Power Flow Controller (DPFC),” International Journal of Power and Applied Mathematics, Vol. 114, No. 8, 2017, pp. 285-297.

      [8] Haadi Sadat, “ Power System Analysis, McGraw Hill Education”, 1999.

      [9] J. Duncan Glover, Mulukutla S. Sarma, Thomas J. Overbye, “Power System Analysis and Design, Fourth Edition, Thomson”, 2008.

      [10] Layth Tawfeeq, “Optimal Power Flow (OPF) with different Objective Function based on modern heuristic optimization techniques,” PhD Thesis, University POLITEHNICA of Bucharest, Romania, 2015.

      [11] Layth Twfeeq, Virgil Dumbrava,“ Optimal Power Flow Based on Particle Swarm Optimization, ” U.P.B. Sci. Bull., Series C, Vol. 78, Iss. 3, 2016.


 

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Article ID: 28061
 
DOI: 10.14419/ijet.v7i4.19.28061




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