Sudan National Grid Contingency Ranking Through Fuzzy Logic Approach
Mohammed Osman Hassan Mohammed Zain1, Israa Salih Hamad Alajab2
1 Dr. Mohammed Osman Hassan, Associate Professor, School of Electrical and Nuclear Engineering, College of Engineering, Sudan University of Science and Technology, Khartoum, Sudan.
2Israa Salih Alajab*, Network Analysis Department, the General Directorate of Planning and Projects, Sudanese Electricity Transmission Company, Khartoum, Sudan.
Manuscript received on 21 February 2022. | Revised Manuscript received on 02 April 2022. | Manuscript published on 30 April 2022. | PP: 1-7 | Volume-9, Issue-4, April 2022. | Retrieval Number: 100.1/ijaent.C0468039322 | DOI: 10.35940/ijaent.C0468.049422
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Abstract: The effect of the line outage when rest of system is stable is called contingency study. The outage on the system may be for single line (N-1) contingency or for multiple lines (N-m) contingency where N the total number of lines and m the number of lines out the service. The study of contingency is essential process in planning, operating and control of power systems. The main thrust of contingency studies carried out in power system control centers is to determine the steady state effects of outages. Large power systems require the analysis of all the credible contingence within a very short time so as to exercise the control in the short time available for corrective action. Generally, the system continues to operate in the contingency condition for a considerable duration of time, on occurrence of a line outage. The altered voltage stability margins of all the load buses for the various contingency conditions are to be known prior to monitor and initiate emergency control action to avoid voltage collapse. This study suggests an intelligent technique using fuzzy logic control system to assist in ranking the single contingency (N-1) which occur in the system. The suggested fuzzy logic approach was taken into consideration and applied to the national Sudanese grid.
Keywords: Contingency Analysis (CA), Fuzzy Inference Systems (FIS), Severity Index Voltage Profile (SIvp), Severity Index of Line Flow (SILF), Composite Index (CI).
Scope of the Article: Fuzzy Logics