Cover
Vol. 13 No. 1 (2017)

Published: July 31, 2017

Pages: 17-31

Original Article

Voltage Collapse Optimization for the Iraqi Extra High Voltage 400 kV Grid based on Particle Swarm Optimization

Wafaa Saeed 1 Layth Tawfeeq
1Department of Electrical Engineering University of Al-Mustanssereiah Baghdad,Iraq
History
  • Received: May 31, 2017
  • Available Online: July 31, 2017
DOI

https://doi.org/10.37917/ijeee.13.1.3

Abstract

The continuously ever-growing demand for the electrical power causing the continuous expansion and complexity of power systems, environmental and economic factors forcing the system to work near the critical limits of stability, so research's stability have become research areas worthy of attention in the resent day. The present work includes two phases: The first one is to determine the Voltage Stability Index for the more insensitive load bus to the voltage collapse in an interconnected power system using fast analyzed method based on separate voltage and current for PQ buses from these of PV buses, while the second phase is to suggested a simulated optimization technique for optimal voltage stability profile all around the power system. The optimization technique is used to adjust the control variables elements: Generator voltage magnitude, active power of PV buses, VAR of shunt capacitor banks and the position of transformers tap with satisfied the limit of the state variables (load voltages, generator reactive power and the active power of the slack bus). These control variables are main effect on the voltage stability profile to reach the peak prospect voltage stable loading with acceptable voltage profile. An optimized voltage collapse based on Particle Swarm Optimization has been tested on both of the IEEE 6 bus system and the Iraqi Extra High Voltage 400 kV Grid 28 bus . To ensure the effectiveness of the optimization technique a comparison between the stability indexes for load buses before and after technical application are presented. Simulation results have been executed using Matlab software). Keyword: Voltage Stability Indicator; voltage collapse; Stability of Extra High Voltage Grid; PSO optimization technique.

References

  1. Snigdha Kulshrestha1, Sachin Yadav2, Akash Stability and Reactive Power Remuneration of Distribution Network Based on Synthesis Load Model,’’ International Journal of Electrical and Electronics Engineers, IJEEE, Volume 07, Issue 01, pp. 130-139, Jan- June 2015,
  2. Muhammad Nizam, Azah Mohammed and Aini Hassain,“Performance Evaluation of Voltage Stability Indices for Dynamics Voltage Collapse Prediction,’’ Journal of Applied Sciences 6 (5), PP. 1104-1113, 2006.
  3. Akwukwaegbu I.O, Okwe Gerald Ibe, “ Load Flow Control and Analytical Assessment of Voltage Stability Index Using Thyristor Controlled Series Capacitor (Tcsc),’’ and Development, IJEEE,Volume 10, Issue 4, PP.07-18, (April 2014).
  4. Navid Ghaffarzadeh, Haniyeh Marefatjou, of the Effect of Facts Devices, Capacitors and Lines Reactance Variations on Voltage Stability Improvement and Load ability Enhancement in Two Area Power System,’’ Engineering (IJAPE) Vol.1, No.3, pp. 145~158, December 2012.
  5. F.A. Althowibi, M.W. Mustafa, “Power System Voltage Stability: Allocations and Voltage Collapse Predictions,’’ Journal of Advanced Research in Electrical, Electronics Name of C.V. Min. limits Max. limits C.V. Optimal C.V. 1.00 1.10 1.0400 1.1000 1.00 1.10 1.0150 1.0350 1.00 1.10 1.0100 1.0391 1.00 1.10 1.0200 1.0455 1.00 1.10 1.0200 1.0000 1.00 1.10 1.0170 1.0698 1.00 1.10 1.0100 1.1000 1.00 1.10 1.0200 1.1000 1.00 1.10 1.0200 1.1000 1.00 1.10 1.0300 1.1000 1.00 1.10 1.0250 1.0906 1.00 1.10 1.0200 1.1000 1.00 1.10 1.0100 1.1000 1.00 1.10 1.0096 1.1000 130.00 472.85 1320 120.00 120.00 50.00 360.32 114.96 169.31 1320 339.88 1250 830.97 840.00 440.00 250.00 TABLE 6 CONTROL VARIABLES (C.V.) OF THE IRAQI EXTRA HIGH VOLTAGE 400 kV GRID and Instrumentation Engineering, Vol. 2,
  6. Abdel-Fatah Ali, Ahmad Eid, and Mamdouh Abdel-Akher, “Online Voltage Instability Detection of Distribution Systems for SmartAutomation and Power Engineering, Published Online, PP. 6’’7-72, May 2012.
  7. A. Venikov, V.A. Stroev, V.I Idelchick, and V.I. Tarasov, “ Estimation of electric power system steady state stability in load flow calculations,’’ IEEE Trans. On PAS, vol. PAS-94, No.3, pp. 1034-041, May 1975.
  8. Y.H Hong, C.T Pan, and W.W Lin, “Fast calculation of voltage stability index,’’ IEEE Trans. on Power Systems,vol.12, No. 4, November 1997.
  9. C.A. Belhadj, M.A. Abido, “An Optimized Fast Voltage Stability Indicator,’’ IEEE Power Tech Conference, Budapest, Hungary, Aug 29-Sep2, 1999.
  10. Yunfei Wang, Iraj Rahimi Pordanjani, Weixing Li, Wilsun Xu, Tongwen Chen, Ebrahim Vaahedi, and Jim Gurney, “Voltage Stability Monitoring Based on the Concept of coupled Single-Port Circuit of Coupled Single-Port Circuit, ’’ IEEE Transactions on Power Systems, May 05, 2011.
  11. Y. Wang, W. Y. Li, and J. P. Lu, “A new node voltage stability index based on local voltage phasors,’’ Elect. Power Syst. Res., vol. 79, pp. 265–271, 2009
  12. A. Wiszniewski, “New criteria of voltage stability margin for the purpose of load shedding, ’’ IEEE Trans. Power Del., vol. 22, no. 3, pp. 1367–1371, Jul. 2007.
  13. M. Moghavvemi and O. Faruque, “Realtime contingency evaluation and ranking technique, ’’ Proc. Inst. Elect. Eng., Gen., Transm., Distrib., vol. 145, no. 5, pp. 517–52 4, Sep. 1998.
  14. I. Smon, G. Verbic, and F. Gubina, “Local voltage-stability using Tellegen’s theorem,” IEEE Trans. Power Syst., vol. 21, no. 3, pp. 1267–1275, Aug. 2006 .
  15. Blamourougan,V.,Sidhu,T.S.,Sachdev,M.S., “Technique for online prediction of voltage collapse, ” IEE Proceedings on Generation, Transmission and Distribution, vol. 145, p. 111, 1998.
  16. Murthy, S. Sivanagaraju, S. Satyanarayana, and B. Hanumantha Rao,“Voltage Stability Analysis of Radial Distribution Network with Distributed Journal of Electrical Engineering and Volume 6, Number1, March 2014.
  17. H.H. Goha, Q.S. Chuaa, S.W. Leea, B.C. Koka, K.C. Goha, K.T.K. Teob, “ Evaluation for Voltage Stability Indices in Power System Using Artificial Neural Network,’’ Procedia Engineering 118, PP. 1127 – 1136, 2015.
  18. P Kessel, H Glavitsch, “Estimating the voltage stability of a power System,’’ IEEE Trans on Power Delivery, vol. PWRD-1, No.3, July, pp. 346-354, 1986.
  19. Wafaa Saeed, Kassim Al-Anbarri, “A Reliable Load Flow Method for Radial Distribution Systems,’’ Journal of Engineering & Development, Vol. 16, No. 2,
  20. Layth T. Al. Bahrani and Virgil Dumbrava,’’Optimal Power Flow based on Particle Swarm Optimization,’’ University POLITEHNICA of Bucharest, Romania Sci. Bull., Series C, Vol. 78, Iss.3, 2016.
  21. Layth T. Al-Bahrani, ‘’Optimal Power Flow (OPF) with different Objective Function based on modern heuristic optimization techniques,’’ PhD Thesis, University POLITEHNICA of Bucharest, Romania, September 2015.
  22. Tiruvuru, Krishna Dist, Andhra Pradesh, Chirala, Guntur Dist, Andhra Pradesh, “ A modified Particle Swarm optimization Technique for Solving Improvement of Voltage Stability and Reduce Power Losses Using upfc,’’ (IJERA), Vol. 2, Issue 3, pp. 1516-1521, May-Jun 2012.
  23. S. Harish Kiran*, Subhransu Sekhar Dash, C. Subramani and Somashree Pathy, “ An Efficient Swarm Optimization Technique for Stability Analysis in IEEE – 14 Bus System, ’’ Indian Journal of Science and Technology, Vol 9(13), April 2016.
  24. Layth T. Al. Bahrani and M. Eremia , ‘’Reactive power optimization based on particle swarm optimization PSO, ’’CIGRE Regional South-East European ConferenceRSEEC 2014 (second edition), Proceeding of RSEEC 2014 Innovation for efficient and effective management, solutions for power system of the future , Timisoara, Romania, 2014.
  25. C. A. Belhad and M. A. Abido ‘’ An optimized fast voltage stability indicator’’
  26. M. A. Abido, ‘’ Multi-objective Optimal VAR Dispatch Using Strength Pareto Evolutionary Algorithm’’, IEEE, Congress on Evolutionary Computation, July 16-21, 2006, Vancouver, BC, Canada . Appendix Table A.1 State variable constraints of IEEE 6 bus Minimum limit Maximum limit PQ bus voltage 0.9 1.10 Table A.2 Line data of IEEE 6 bus Branch No. From bus To bus Branch impedance p.u Transformer Tap 0.123+j0.518 0.080+j0.370 0.097+j0.407 0.282+j0.640 0.723+j1.050 0.000+j0.300 1.025 0.000+j0.133 1.100 Table A.3 Bus data of IEEE 6 bus Bus No. Bus type Bus voltage p.u Angle degree Load Shunt injection capacitance MVAR MW MVAR MW MVAR Slack 1.05 PU 1.10 PQ PQ PQ PQ Table A.4 State variable constraints of the Iraqi Extra High Voltage 400 kV Minimum limit Maximum limit PQ bus voltage 0.9 1.10 Table A.5 Bus data of the Iraqi Extra High Voltage 400 kV Bus No. Bus Name Bus type Bus voltage p.u Load MW MVAR MW MVAR MUSP Slack 1.040∟ MMDH PV 1.015∟ NENWG PV 1.010∟ BAJP PV 1.015∟ BAJG PV 1.020∟ KRK4 PV 1.017∟ QDSG PV 1.010∟ HDTH PV 1.020∟ MUSG PV 1.020∟ KUTP PV 1.030∟ KHRPG PV 1.025∟ NSRP PV 1.020∟ HRTHP PV 1.010∟ KAZG PV 1.0096∟ MSL4 PQ 1∟ BGS4 PQ 1∟ BGW4 PQ 1∟ BGE4 PQ 1∟ BGN4 PQ 1∟ AMN4 PQ 1∟ BGC4 PQ 1∟ DYL4 PQ 1∟ KUT4 PQ 1∟ QIM4 PQ 1∟ BAB4 PQ 1∟ KDS4 PQ 1∟ AMR4 PQ 1∟ BSR4 PQ 1∟ Table A.6 Line data of the Iraqi Extra High Voltage 400 kV No. of branches From bus To bus Resistance p.u Reactance p.u Half line charging Susceptance (p.u) Length of the line km 0.00144 0.01177 0.364390 0.001440 0.011770 0.364390 0.001777 0.016154 0.478634 0.004200 0.03437 1.064260 0.004984 0.045310 1.342510 0.003294 0.029940 0.887224 0.000020 0.000200 0.005840 0.004830 0.043930 1.301650 0.004960 0.045110 1.336670 0.003450 0.031320 0.928080 0.001800 0.016350 0.484470 0.004960 0.045110 1.333667 0.000930 0.008470 0.250990 0.000607 0.005516 0.163436 0.005049 0.045901 1.360021 0.000820 0.007490 0.221810 0.000820 0.007490 0.221810 0.000953 0.008660 0.256820 0.001220 0.010150 0.318970 53.5 0.001094 0.009106 0.286176 0.003080 0.027950 0.828270 141.9 0.000290 0.002620 0.077630 13.3 0.000430 0.003940 0.116740 0.000870 0.007880 0.233480 0.000150 0.001380 0.040860 0.002427 0.022064 0.653744 0.001734 0.015760 0.466960 0.004320 0.039280 1.163900 199.4 0.004790 0.043540 1.289980 0.002920 0.023910 0.740350 0.000125 0.001043 0.032791 5.5 0.000810 0.006730 0.211650 35.5 0.000810 0.006730 0.211650 35.5 0.000898 0.007360 0.227000 39.4 0.002330 0.019350 0.608120 0.002267 0.018500 0.575200 99.45 0.003830 0.034850 1.032560 176.9 0.004390 0.039930 1.183160 202.7 0.002900 0.026400 0.782160 0.001180 0.010760 0.318700 54.6 0.001180 0.010760 0.318700 54.6 0.000672 0.006107 0.180947 0.000563 0.005122 0.151762