Journal of Electrical Engineering and Technology

The Korean Institute of Electrical Engineers (대한전기학회)
권호 표지
DOI QR코드

DOI QR Code

Congestion Management in Deregulated Power System by Optimal Choice and Allocation of FACTS Controllers Using Multi-Objective Genetic Algorithm

  • Reddy, S. Surender (Dept. of Electrical Engineering, National Institute of Technology) ;
  • Kumari, M. Sailaja (Dept. of Electrical Engineering, National Institute of Technology) ;
  • Sydulu, M. (Dept. of Electrical Engineering, National Institute of Technology)
  • Published : 2009.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

Congestion management is one of the technical challenges in power system deregulation. This paper presents single objective and multi-objective optimization approaches for optimal choice, location and size of Static Var Compensators (SVC) and Thyristor Controlled Series Capacitors (TCSC) in deregulated power system to improve branch loading (minimize congestion), improve voltage stability and reduce line losses. Though FACTS controllers offer many advantages, their installation cost is very high. Hence Independent System Operator (ISO) has to locate them optimally to satisfy a desired objective. This paper presents optimal location of FACTS controllers considering branch loading (BL), voltage stability (VS) and loss minimization (LM) as objectives at once using GA. It is observed that the locations that are most favorable with respect to one objective are not suitable locations with respect to other two objectives. Later these competing objectives are optimized simultaneously considering two and three objectives at a time using multi-objective Strength Pareto Evolutionary Algorithms (SPEA). The developed algorithms are tested on IEEE 30 bus system. Various cases like i) uniform line loading ii) line outage iii) bilateral and multilateral transactions between source and sink nodes have been considered to create congestion in the system. The developed algorithms show effective locations for all the cases considered for both single and multiobjective optimization studies.

Keywords

References

  1. N. G. Hingorani and L. Gyugyi, 'U nderstanding FACTS: Concepts and Technology of Flexible AC Transmission Systems', IEEE Press, 1999
  2. F, D, Galiana, K. Almeida, M. Toussaint, J. Griffin, and D. Atanackovic, ' Assessment and control of thε impact of F ACTS devices on power system performance,' lEEE Trans. Power Systems, vol. 11, no. 4, Nov. 1996
  3. S. Gerbex, R. Cherkaoui ， and A. J. Germond, 'Optimallocation of multi type F ACTS devices in a power system by means of genetic algorithms,' lEEE Trans. Power Systems, vol. 16, pp. 537-544, 2001 https://doi.org/10.1109/59.932292
  4. S.N.Singh and A.K.David, 'Congεstion Managεment by optimizing F ACTS devices location' ,IEEE Power Engineering Review, pp.58-60, September 2000
  5. Keshi Reddy Saidi Reddy, Narayana Prasad Padhy， and R.N.Patel, Congestion Management in Deregulated Power System using F ACTS devices' ,IEEE Power lndia Conference， 2006
  6. Kalyanmoy Deb, 'Multi-objective Optimization using Evolutionary algorithms', John Wiley and Sons, 2001
  7. Ajith Abraham, Lakhmi lain, Robert oldberg (Eds), ' Evolutionary Multi-objective Optimization, Theoretical Advances and Applications,'Springer-Verlag London limited,2005
  8. Abido.M.A, ' EnvironmentallEconomic Power Dispatch using Multiobjective Evolutionary Algorithms',IEEE Trans. on Power Systems, vol. 18, No.4, pp.1529-1537,November, 2003 https://doi.org/10.1109/TPWRS.2003.818693
  9. Abido.M.A., J.M.Bakhashwain, ' Optimal VAR Dispatch using a Multi-objective Evolutionary algorithm', Electric Power and Energy systems, vol. 27, pp.13-20, 2005 https://doi.org/10.1016/j.ijepes.2004.07.006
  10. IEEE Special Stability Controls Working Group, ' Static V AR Compensator Models for Power flow and Dynamic Performance simulation', lEEE Trans on Power Systems, vol.9, No.1, pp. 229-240, February 1994 https://doi.org/10.1109/59.317606
  11. H.Ambriz-perez, E.Acha and C.R. Fuerte-Esquivel, ' Advanced SVC modεIs for Newton-Raphson load flow and Newton Optimal Power flow studies', lEEE Trans.On Power Systems, vol. 15, No.1 ，’ pp.129-136 Feb.2000 https://doi.org/10.1109/59.852111
  12. L.J.Cay, I.Erlich, ' Optimal choice and allocation of F ACTS devices using Genetic Algorithms" ,IEEE PES Power Systems Conference and Exposition, pp.201-207,2004
  13. M.Saravanam， S.MaryRajaSlochanal，V.Venkatεsh， Pri nce Stephen Abraham.J, ' Application of PSO technique for optimal location of F ACTS devices considering system loadability and cost of installation',IPEC Power Engineering Conference， pp.716-721 ,2005
  14. l .G.Singh, S.N.Singh and S.C.Srivastava, ' Placement of FACTS controllεrs for enhancing Power System Loadability', IEEE Power India Conference, 2006
  15. lames A.Momoh, M.E.EI-Hawary, Rambabu Adapa, 'A Review of Selected Optimal Power Flow Literature to 1993 Part-I: Non-linεar and Quadratic Programming approaches', lEEE Trans. on Power Systems, Vol. 14, No.1 , pp. 96-104, February 1999 https://doi.org/10.1109/59.744492

Cited by

  1. Congestion Management in Deregulated Power System Using Heuristic Search Algorithms Incorporating Wireless Technology vol.94, pp.4, 2017, https://doi.org/10.1007/s11277-016-3878-4
  2. Game model-based co-evolutionary algorithm with non-dominated memory and Euclidean distance selection mechanisms for multi-objective optimization vol.9, pp.5, 2011, https://doi.org/10.1007/s12555-011-0513-8
  3. Congestion management in power systems – A review vol.70, 2015, https://doi.org/10.1016/j.ijepes.2015.01.022
  4. Mitigating Congestion in a Power System and Role of FACTS Devices vol.2017, 2017, https://doi.org/10.1155/2017/4862428
  5. Investigation of TCSC Controller Effect on IDMT Directional Over-current Relay vol.195, 2015, https://doi.org/10.1016/j.sbspro.2015.06.250