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|Contingency Analysis in Power System
|Roy, Amit Kumar
|Jain, Sanjay Kumar
|Contingency Analysis;Contingency Selection;Fast Decoupled Load Flow;Performance Index;Radial Basis Function;ANN
|Maintaining power system security is one of the challenging tasks for the power system engineers. The security assessment is an essential task as it gives the knowledge about the system state in the event of a contingency. Contingency analysis technique is being widely used to predict the effect of outages like failures of equipment, transmission line etc, and to take necessary actions to keep the power system secure and reliable. The off line analysis to predict the effect of individual contingency is a tedious task as a power system contains large number of components. Practically, only selected contingencies will lead to severe conditions in power system. The process of identifying these severe contingencies is referred as contingency selection and this can be done by calculating performance indices for each contingencies. The main motivation of the work is to carry out the contingency selection by calculating the two kinds of performance indices; active performance index (PIP) and reactive power performance index (PIV) for single transmission line outage. With the help of Fast Decoupled Load Flow (FDLF), the PIP and PIV have been calculated in MATLAB environment and contingency ranking is made. Further the contingency selection has been done by using Radial Basis Function (RBF) Neural Network. This provides an effective mean to rank the contingencies for various loading and generation levels in a power system. The effectiveness of the method has been tested on 5-Bus, IEEE-14 Bus and IEEE-30 Bus test systems.
|M.E. (Power Systems and Electric Drives)
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|Amit Kumar Roy (800941003) 19-8.pdf
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