GABC optimization algorithm for solving simultaneous transmission expansion planning and substation expansion planning

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Published Jul 2, 2015
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Volume 11, Issue 3, September 2015

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Chandrakant Rathore
Research scholar, Electrical Engineering Department, S.V. National Institute of Technology, Suart - 395007

Abstract

This paper presents the Gbest-guided Artificial Bee Colony (GABC) optimization technique for solving the transmission and substation expansion planning simultaneously. The motive of the proposed approach is to minimize the summation of the Transmission line Investment Cost (TIC) and the Operation Cost (OC). The OC is the combination of the fuel cost of generating units and the total wind power uncertainty cost (TWC). To reduce the power demand now-a-days more renewable energy resources are integrating in the system by the system operator. Hence, this work also adopted the wind power uncertainty factor. The DC power flow model is used to formulate the mathematical structure of Simultaneous Transmission and Substation Expansion Planning (STSEP) problem. To have more complexity on the proposed problem load uncertainties are also considered. The proposed model is tested on the modified IEEE 24-bus reliability test system. Different case studies are considered to demonstrate the effectiveness of the adopted study. Detailed analyses on the numerical results are briefly presented. The results obtained indicate that with load variations the total cost of the system has increased, as well as the selection of lines and substations have also varied.

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How to Cite
Rathore, C. (2015). GABC optimization algorithm for solving simultaneous transmission expansion planning and substation expansion planning. Power Research - A Journal of CPRI, 455–468. Retrieved from https://cprijournal.in/index.php/pr/article/view/702

References

  1. F F Wua, F L Zhengb, and F S Wen, Transmission investment and expansion planning in a restructured electricity market, Energy, Vol. 31, pp. 954-966, 2006.
  2. M S Sepasian, H Seifi, A A Foroud, S H Hosseini, and E M Kabir, A new approach for substation expansion planning, IEEE Trans. PS, Vol. 21, pp. 997-1004, 2006.
  3. L L Garver, Transmission network estimation using linear programming, IEEE Trans. PS, Vol-89, pp. 1688-1697, 1970.
  4. G Latorre, R D Cruz, and M Areiza, A Villegas, Classification of publications and models on transmission expansion planning, IEEE Trans. PS, Vol. 18, pp. 938-946, 2003.
  5. R Hemmati, and R A Hooshmand, and A Khodabakhshian, State-of-the-art of transmission expansion planning: Comprehensive review, Rene. Sust. Energy Rev., Vol. 23, pp. 312–319, 2013.
  6. S Sarhadi, and T Amraee, Robust dynamic network expansion planning considering load uncertainty, Int. J Electr. Power Energy Syst., Vol.71, pp. 140-150, 2015.
  7. I M Mendonça, I C S Junior, and A L Marcato, Static planning of the expansion of electrical energy transmission systems using particle swarm optimization, Int. J Electr. Power Energy Syst., Vol. 60, pp. 234-244, 2014.
  8. R C Leou, A multi-year transmission planning under a deregulated market, Int. J Electr. Power Energy Syst., Vol. 33, pp. 708-714, 2011.
  9. D Delgado, and J Claro, Transmission network expansion planning under demand uncertainty and risk aversion, Int. J Electr. Power Energy Syst., Vol. 44, pp. 696–702, 2013.
  10. W Wangdee, and R Billinton, Reliability assessment of bulk electric systems containing large wind farms, Int. J Electr. Power Energy Syst., Vol. 29, pp. 759–766, 2007.
  11. Y Gu, J D McCalley, and M Ni, Coordinating Large-Scale Wind Integration and Transmission Planning, IEEE Trans. SE, Vol. 3, pp. 652-659, 2002.
  12. C Rathore, and R Roy, A novel modified GBMO algorithm based static transmission network expansion planning, Int. J Electr. Power Energy Syst., Vol. 62, pp. 519-531, 2014.
  13. M R Haghifam, and M Shahabi, Optimal location and sizing of HV/MV substations in uncertainty load environment using genetic algorithm, Electr. Power Syst. Res., Vol. 63, pp. 37-50, 2002.
  14. M Jalali, K Zare, and M T Hagh,A multistage MINLP-based model for subtransmission system expansion planning considering the placement of DG units, Int. J Electr. Power Energy Syst., Vol. 63, pp. 8-16, 2014.
  15. T Akbari, M Heidarizadeh, M A Siab and M Abroshan, Towards integrated planning: Simultaneous transmission and substation expansion planning, Electr. Power Syst. Res., Vol. 86, pp. 131-139, 2012.
  16. B Basturk, and D Karaboga, A powerful and efficient algorithm for numerical function optimization, artificial bee colony (ABC) algorithm, J Global Opt., Vol. 39, pp. 459-471, 2007.
  17. W Gao, S Liu, and L Huang, A global best artificial bee colony algorithm for global optimization, J Comput. Appl. Math., Vol. 236, pp. 2741-2753, 2012.
  18. G Zhu, and S Kwong, Gbest-guided artificial bee colony algorithm for numerical function optimization, Appl. Math. Comput., Vol. 217, pp. 3166-3173, 2010.
  19. N K Garg, S S Jadon, H Sharma, and D K Palwalia, Gbest-Artificial Bee Colony Algorithm to Solve Load Flow Problem, In Proc of the Third Int. Confer. Soft Comput. for Problem Solving, Springer India, 2014 January, pp. 529-538.
  20. M Govardhan, and R Roy, Generation scheduling in smart grid environment using global best artificial bee colony algorithm,Int. J Electr. Power Energy Syst., Vol. 64, pp. 260-274, 2015.
  21. H T Jadhav and R Roy, Gbest guided artificial bee colony algorithm for environmental / economic dispatch considering wind power, Exp. Syst. Appl., Vol. 40, pp. 6385-6399, 2013.
  22. R Romero, C Rocha, J R S Mantovani, and I G Sanchez, Constructive heuristic algorithm for the DC model in network transmission expansion planning, IET Proc. Gener. Trans. Distrib., Vol. 152, pp. 277-282, 2005.
  23. R Fang, and D J Hill, A new strategy for transmission expansion in competitive electricity markets, IEEE Trans. PS, Vol. 18, pp. 374-380, 2003.
  24. I J Silva, M J Rider, R Romero, A V Garcia, and CA Murari, Transmission network expansion planning with security constraints, IET Proc. Gener. Trans. Distrib., Vol. 152, pp. 828-836, 2005.
  25. G R Kamyab, M Fotuhi-Firuzabad, and M Rashidinejad, A PSO based approach for multi-stage transmission expansion planning in electricity markets, Int. J Electr. Power Energy Syst., Vol. 54, pp. 91-100, 2014.
  26. [Online].Available, http://pscal.ece.gatech.edu/archive/testsys/generators.html
  27. J Hetzer, Y David C, and K Bhattarai, An economic dispatch model incorporating wind power, IEEE Trans. EC, Vol. 23, pp. 603-611, 2008.
  28. Y F L Isaac, and C L Joseph, A study of Weibull parameters using long-term wind observations, Rene. Energy, Vol. 20, pp. 145-153, 2000.
  29. R Romero, E N Asada, E Carreno, and C Rocha, Constructive heuristic algorithm in a branch-and-bound applied to transmission network expansion planning, IET Proc. Gener. Trans. Distrib., Vol. 1, pp. 318-323, 2007.