A. Y. Abdelaziz; A. T. M. Taha; M. A. Mostafa; A. M. Hassan

Fuzzy Logic Based Power System Contingency Ranking

Full Text (PDF, 559KB), PP.1-12

Views: 0 Downloads: 0

Author(s)

A. Y. Abdelaziz ^1,* A. T. M. Taha ¹ M. A. Mostafa ¹ A. M. Hassan ¹

1. Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2013.03.01

Received: 20 May 2012 / Revised: 4 Sep. 2012 / Accepted: 10 Nov. 2012 / Published: 8 Feb. 2013

Index Terms

Contingency Ranking, Fuzzy Sets, Line Flow Index, FVSI, Criticality Index

Abstract

Voltage stability is a major concern in planning and operations of power systems. It is well known that voltage instability and collapse have led to major system failures. Modern transmission networks are more heavily loaded than ever before to meet the growing demand. One of the major consequences resulted from such a stressed system is voltage collapse or instability. This paper presents maximum loadability identification of a load bus in a power transmission network. In this study, Fast Voltage Stability Index (FVSI) is utilized as the indicator of the maximum loadability termed as Qmax. In this technique, reactive power loading will be increased gradually at particular load bus until the FVSI reaches close to unity. Therefore, a critical value of FVSI was set as the maximum loadability point. This value ensures the system from entering voltage-collapse region. The main purpose in the maximum loadability assessment is to plan for the maximum allowable load value to avoid voltage collapse; which is important in power system planning risk assessment.
The most important task in security analysis is the problem of identifying the critical contingencies from a large list of credible contingencies and ranks them according to their severity. The condition of voltage stability in a power system can be characterized by the use of voltage stability indices. This paper presents fuzzy approach for ranking the contingencies using composite-index based on parallel operated fuzzy inference engine. The Line Flow index (L.F) and bus Voltage Magnitude (VM) of the load buses are expressed in fuzzy set notation. Further, they are evaluated using Fuzzy rules to obtain overall Criticality Index. Contingencies are ranked based on decreasing order of Criticality Index and then provides the comparison of ranking obtained with FVSI method.

Cite This Paper

A. Y. Abdelaziz, A. T. M. Taha, M. A. Mostafa, A. M. Hassan, "Fuzzy Logic Based Power System Contingency Ranking", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.3, pp.1-12, 2013.DOI:10.5815/ijisa.2013.03.01

Reference

[1]Andersson, G.; Donalek "Causes of the 2003 major grid blackouts in North America and Europe, and recommended means to improve system dynamic performance", Power Systems, IEEE Transactions on Volume 20, Nov. 2005, pp. 1922 - 1928.

[2]Pimjaipong, W.; Junrussa "Blackout Prevention Plan – The Stability, Reliability and Security Enhancement in Thailand Power Grid", Transmission and Distribution Conference and Exhibition: Asia and Pacific, 2005 IEEE/PES 2005, pp. l - 6.

[3]IEEE Committee Report, "Voltage stability of power systems: Concepts, analytical tools and industrial experiences," IEEE Publication No. 90TH0358- 2-PWR, New York, 1990.

[4]Qiuxia Yu et al, “Adaptability evaluation of transmission network planning under deregulation,” Universities Power Engineering Conference, 2007. UPEC 2007. 42nd International pp. 53-56, 4-6 September 2007

[5]Scott Greene, Ian Dobson and Fernanado L. Alvarado, “Contingency Ranking for Voltage Collapse via Sensitivities from a Single Nose Curve”, IEEE Transactions on Power Systems, Vol.14, No.1, pp. 232-239, Feb 1999.

[6]R. A. Alammari, “Fuzzy System Applications for Identification of Weak Buses in Power Systems”, The Arabian Journal for Science and Engineering, Vol. 27, No. 2B, Oct. 2002.

[7]Y.Y. Hong and C.H. Gau, “Voltage Stability Indicator for Identification of the Weakest Bus Area in Power Systems”, IEE Proceedings Generation Transmission Distribution, Vol. 144, No. 4, July 1994.

[8]I. Musirin and T.K. Abdul Rahman, “Estimating maximum loadability of weak bus identification using FVSI”, IEEE Power Engineering Review, Nov. 2002.

[9]Y.L. Chen, “Weak Bus-Oriented Optimal Multi- objective VAR Planning”, IEEE Transactions on power system, Vol.11, No.4, Nov. 1996.

[10]Y.H. Song H.B. Wan, “Kohonen neural network based approach to voltage weak buses/area identification”, IEE Proceedings Generation Transmission Distribution, Vol. 144, No. 3, May, 1997.

[11]I. Musirin, “Novel Fast Voltage Stability Index (FVSI) for Voltage Stability Analysis in Power Transmission System”, Conference on Research and Development Proceedings, Shah Alam, Malasia, July 2002.

[12]M. Moghavvemi, O. Faruque “Real-Time Contingency Evaluation and Ranking Technique”, IEEE Proceeding on Generation, Transmission and Distribution, Vol. 145, N5, September 1998.

[13]Power System Test Case Archive. Available from: www.ee.washington.edu.

[14]L.Cox, The Fuzzy systems handbook, 2nd, academic press, new york, 1999.

[15]T. Terano, K. Asai, M. Sugeno, Fuzzy system theory and it’s application academic press, San Diego, 1991.

[16]Shobha Shankar, Fuzzy Approach to Contingency Ranking, International Journal of Recent Trends in Engineering, Vol. 1, No. 1, May 2009

International Journal of Intelligent Systems and Applications (IJISA)