FUZZY CONGESTION-DRIVEN AND SENSITIVITY ANALYSIS BASED HEURISTIC TRANSMISSION EXPANSION PLANNING METHOD

Abstract

Transmission expansion planning provides an essential measure for long-term congestion management. Congestion-driven planning method becomes one of the new challenges under deregulated environment. With POOL transaction pattern being the basic investigation background, the fuzzy congestion management models for bilateral auction market mode and single-buyer market mode are set up first in this paper. The soft constraints of line power flow limits, and market participants' bidding curve coefficients considering possible strategic bidding, are all described in form of fuzzy membership functions. Second, based on the maximum membership rule and maximum entropy principle, the fuzzy optimal congestion management problem is solved. New sensitivity indexes to select to-be-built or to-be-upgraded lines are defined for the two market modes respectively. They describe the compromise between congestion relieving impact and investments, and make the problem of transmission network planning solved fast, simple and heuristic. Test results illustrates that the fuzzy congestion-driven and sensitivity analysis based heuristic transmission network planning method for POOL transaction pattern presented by this paper is robust and practical under the deregulated environment.

Keywords

• Congestion managemen, Heuristic transmission expansion planning, Electricity markets, Fuzzy set theory, Maximum entropy principle

References

1. C. Cagigas, M. Madriga., “Centralized vs. Competitive Transmission Expansion Planning: the Need for New Tools”, IEEE Power Engineering Society General Meeting, Vol: , pp. 1012-1017, July 2003 .
2. Xu Lin, Yu Yixin, Liu Huaidong, Lu Fang, Zhang Yun, Huang Yaogui, “Double-Sided Transmission Congestion Management and Quasi-Aumann-Shapley Pricing”, Proceedings of the CSEE, Vol: 22, No: 10, pp. 56-60, 2002.
3. E. F. Sanchez-Ubeda, J. Peco, P. Raymont., T. Gomez, S. Banales, A. L. Hernandez, “ Application of data mining techniques to identify structural congestion problems under uncertainty”, IEEE Power Tech Proceedings, Porto, Vol: 1, pp. 6-11, Sept. 2001.
4. G. B. Shrestha, P. A. J. Fonseka, “ Congestion-Driven Transmission Expansion in Competitive Power Markets”, IEEE Trans. on Power Systems, Vol: 19, No: 3, pp. 1-8, Aug. K. Y. Lee, S. Manuspiya, Choi Myeonsong, Myongchul Shin, “Network Congestion Assessment for Short-term Transmission Planning under Deregulated Environment”, IEEE Power Engineering Society Winter Meeting, Columbus, Ohio USA, Vol: 3, pp. 1266-1271, Jan. 2001.
5. Sun Hongbo, Xu Guoyu, Qin Yihong, Zhao Youxin, “the Fuzzy Stochastic Optimization Model for Power Network Planning”, Power System Technology, Vol: 25, No: 5, pp. 4-7, Yang Hongming, Duan Xianzhong, “Bilateral Transmission Curtailment Model Based on Fuzzy Theory”, Automation of Electric Power systems, Vol: 26, No: 20, pp. 24-28, 2002.
6. Li Xingsi, “An Effective Solving Method for a Class of Nondifferential Optimization Problems”, Science in China (Series A), Vol: 24, No: 4, pp. 371-377, 1994.
7. He hui, Xu zheng, Huang Ying, “The Role of Load in Transmission Congestion Management”, Automation of Electric Power systems, Vol: 27, No: 17, pp. 11-14, 2003.