Design and Implementation of Power System Optimization Using Particles Swarm Algorithms

This study aims to develop a power system optimization simulation environment for one of Electrical Supply Grid in Peshawar Region where theoretical, calculated and collected data is used and proposes enhancements in the distribution system as per the results of the simulation of the Particle Swarm Optimizer and Newton Rhapson Algorithm on it. The simulation framework is cross-evaluated on the IEEE-30 Bus bar system and compared with eminent researches in this field. The results are plotted and tabulated first as a comparison and then as a proposed model for Peshawar Region’s selected substations and the involved grid.

1. Engr. Haleem Zahir Shah is M.Sc research scholar in Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan. Cell: 0092-3348908901 E-mail: haleemzahir@yahoo.com
2. Dr. Muhammad Naeem Arbab  is Professor in Department of Electrical Engineering, University of Engineering and Technology, Peshawar, Pakistan. Cell: 0092-333-9108908, E-mail: mnarbab@yahoo.com

Engr. Haleem Zahir Shah, Dr. Muhammad Naeem Arbab, "Design and Implementation of Power System Optimization Using Particles Swarm Algorithms" International Journal of Engineering Works, Vol. 4, Issue 10, PP. 196-103, October 2017. 

1. [1]     N.G. Hingorani and L. Gyugyi, understanding FACTS: concept & technology of flexible AC transmission system, IEEE press, 2000
2. [2]     H.F. Wang, F. J. Swift, FACTS–based stabilizer designed by the phase compensation method part I on single machine power system, advance in power system control, operation & management, 1997. APSCOM-97, fourth international conference on 11-14 Nov. 1997
3. [3]     Richard C. dorf, Modern control system, Addison wesley publishing company, 1992.
4. [4]     K.R. Padiyar, power system dynamics stability and control, BS publications, 2nd edition, Hederabad, India 2002.
5. [5]     R. M. Mathur and R. K.Verma, thyristor-based FACTS controllers for electrical transmission system, IEEE press, Piscataway,
6. [6]     R. Narmatha Banu and D. Devraj, ‘GA approach for optimal power flow with FACTS devices” 4th International IEEE Conference on intelligent systems.
7. [7]     H.D. Mathur and S. Ghosh, “A comprehensive analysis of intelligent control for load frequency control”, IEEE Power India conference, 2006.
8. [8]     D. M. Vinod Kumar, “Intelligent Controllers for Automatic Generation Control”, Proc. Of IEEE region 10 International conference on global connectivity in Energy, Computer, Communication and Control, 1998, pp557-574.
9. [9]     P. Kundar, “Power System Stability and Control”, Tata Mcgraw Hill, Newyork, 1994.
10. [10]  Haluk GOZDE et al, PSO based Load Frequency Control in a single area power system, University of Pitesti, Scientific Bulletin, Vol.2, No.8, 2008, pp106-110.
11. [11]  Kaur H.,Brar Y.S. and Randhawa J.S., Optimal Power Flow Using Power World Simulator  IEEE Electrical Power & Energy Conference , s. 1 -2, 2010.
12. [12]  C. Sumpavakup, I. Srikun, and S. Chusanapiputt, “A Solution to the Optimal Power Flow Using Artificial Bee Colony Algorithm”, International Conference on Power System Technology, 978-J-4244-5940-7/10/, Tailand, 2011 .
13. [13]  X. Tong and M. Lin, “Semismooth Newtontype Algorithms for Solving Optimal Power Flow Problems”, in Proc. Of IEEE/PES Transmission and Distribution Conference, Dalian, China, pp.l-7, 2005.
14. [14]  R.N. Banu and D. Devaraj, “Optimal Power Flow for Steady State Security Enhancement Using Genetic Algorithm with FACTS Devices”, 3rd International Conference on Industrial and Information Systems, pp. 1 – 6, 8-10 December 2008.
15. [15]  L.L. Lai and J.T. Ma, “Power Flow Control in FACTS Using Evolutionary Programming”, IEEE International Conference on Evolutionary Computation, pp. 10, 29 November-1 December 1995.
16. [16]  C. Gonggui and Y. Junjjie, “A new particle Swarm Optimization Solution to Optimal Reactive Power Flow Problem”, Asia-Pacific Power and Energy Engineering Conference, pp.1 – 4, 27-31 March 2009.
17. [17]  L. Weibing, L. Min and W. Xianjia, “An Improved Particle Swarm Optimization Algorithm for Optimal Power Flow”, IEEE 6th International Power Electronics and Motion Control Conference 2009, pp. 2448 – 2450, 17-20 May 2009.
18. [18]  W. Cui-Ru, Y. He-Jin, H. Zhi-Qiang, Z. Jiang-Wei and S. Chen-Jun, “A Modified Particle swarm Optimization Algorithm and its Application in Optimal Power Flow Problem”, International Conference on Machine Learning and Cybernetics 2005, pp. 2885 – 2889, 18-21 August 2005.
19. [19]  S. M. Kumari, G. Priyanka and M. Sydulu, “Comparison of Genetic Algorithms and Particle Swarm Optimization for Optimal Power Flow Including FACTS devices”, IEEE Power Tech 2007, pp. 1105 - 1110, 1 -5 July 2007