A. M. Hassan

Work place: Electrical Power and Machines Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt

E-mail: a.mostafa1894@gmail.com

Website:

Research Interests: Computer systems and computational processes, Artificial Intelligence, Planning and Scheduling, Computer Architecture and Organization, Systems Architecture, Data Structures and Algorithms

Biography

A. M. Hassan was born in Riyadh, KSA   in 1982. He received the B. Eng. Degree and M. Sc. in electrical engineering from Ain Shams University in Cairo, Egypt in 2004 and 2012, respectively. Currently he is an electrical engineer in Badr El Din Petroleum Company (BAPETCO). His research interests include the application of artificial intelligent techniques to power systems operation, protection and planning.

Author Articles
Fuzzy Logic Based Power System Contingency Ranking

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

DOI: https://doi.org/10.5815/ijisa.2013.03.01, Pub. Date: 8 Feb. 2013

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.

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