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A Study on the Rescheduling of Generation Considering Contingency in Power System with Wind Farms

풍력발전단지가 연계된 전력계통에서 상정고장을 고려한 발전력 재조정에 관한 연구

  • Choi, Soo-Hyun (Dept. of Electrical Engineering, Hankyong National University) ;
  • Kim, Kyu-Ho (Dept. of Electrical Engineering, Hankyong National University, IT Fusion Research Institute)
  • Received : 2016.12.29
  • Accepted : 2017.01.19
  • Published : 2017.02.01

Abstract

This paper studies on effective rescheduling of generation when the single line contingency has occurred in power system with wind farm. The suggested method is formulated to minimize the rescheduling cost of conventional and wind generators to alleviate congestion. The generator rescheduling method has been used with incorporation of wind farms in the power system. Since all sensitivity is different about congestion line, Line Outage Distribution Factor(LODF) and Generator Sensitivity Factor(GSF) is used to alleviate congestion. The formulation have been proccessed using linear programming(LP) optimization techniques to alleviate transmission congestion. The effectiveness of the proposed rescheduling of generation method has been analyzed on revised IEEE 30-bus systems.

Keywords

References

  1. Murphy, Colleen, and Andrew Keane. "Optimisation of wind farm reactive power for congestion management." PowerTech (POWERTECH), 2013 IEEE Grenoble. IEEE, 2013.
  2. A. Kumar, S. C. Srivastava, and S. N. Singh, "Congestion management in competitive power market: A bibliographical survey," Elect. Power Syst. Res, vol. 76, pp. 153-164, 2005. https://doi.org/10.1016/j.epsr.2005.05.001
  3. Hazra and Sinha, "Congestion Management Using Multiobjective Particle Swarm Optimization." IEEE transactions on power systems. 22(4), 1726-34 , 2007. https://doi.org/10.1109/TPWRS.2007.907532
  4. Dutta and Singh, "Optimal Rescheduling of Generators for Congestion Management Based on Particle Swarm Optimization." IEEE transactions on power systems. 23(4), 1560-69, 2008. https://doi.org/10.1109/TPWRS.2008.922647
  5. Venkaiah, Ch., and Vinodkumar, D.M, "Fuzzy adaptive bacterial foraging congestion management using sensitivity based optimal active power rescheduling of generators." Applied Soft Computing, 11, 4921-4930, 2011. https://doi.org/10.1016/j.asoc.2011.06.007
  6. Singh, K., Padhy, N.P., and Sharma, J, "Congestion management considering hydro-thermal combined operation in a pool based electricity market." Electrical Power and Energy Systems, 33, 1513-1519, 2011. https://doi.org/10.1016/j.ijepes.2011.06.037
  7. A. Kumar, S. C. Srivastava, and S. N. Singh, "A zonal congestion management approach using real and reactive power rescheduling," IEEE Trans. Power Syst., vol. 19, no. 1, pp. 554-562, Feb. 2004.
  8. Kyu-Ho Kim, et al. "An efficient operation of a micro grid using heuristic optimization techniques: Harmony search algorithm, PSO, and GA." IEEE PES General Meeting, 2012.
  9. Kyung-bin Song, Kyu-Hyung Lim, Young-Sik Baek, "A Case Study of the Congestion Management for the Power System of the Korea Electric Power Cooperation", KIEE, vol. 50A, no. 12, 2001
  10. Allen J. Wood, Bruce F. Wollenberg, "Power generation, operation, and control" Wiley-Interscience, 2002