Power system contingency ranking using Newton Raphson load flow method and its prediction using soft computing techniques

Naik, P (2014) Power system contingency ranking using Newton Raphson load flow method and its prediction using soft computing techniques. MTech thesis.



The most important requirement and need of proper operation of power system is maintenance of the system security. Power system security assessment helps in monitoring and in giving up to date analysis regarding currents, bus voltages, power flows, status of circuit breaker, etc. This system assessment has been done in offline mode in which the system conditions are determined using ac power flows. The use of AC power flows is it gives information of power flows in terms of MW and MVAR , line over loadings and voltage limit violation with accurate values. Contingency selection or contingency screening is a process in which probable and potential critical contingencies are identified for which it requires consideration of each line or generator outage. . Contingency ranking is a procedure of contingency analysis in which contingencies are arranged in descending order, sorted out by the severity of contingency. Overall severity index (OPI) is calculated for determining the ranking of contingency. Overall performance index is the summation of two performance index , one of the performance index determines line overloading and other performance index determines bus voltage drop limit violation and are known as active power performance index and voltage performance index respectively. Here in this proposed work the contingency ranking has been done with IEEE 5 bus and 14 bus system. But the system parameters are dynamic in nature, keeps on changing and may affect the system parameters that are why there is need of soft computing techniques for the prediction purpose. Fuzzy logic approach has also been used. Two model of Artificial Neural Network namely, Multi Layer Feed Forward Neural Network (MFNN) and Radial Basis Function Network (RBFNN) have been considered. With these soft computing techniques the prediction method helps in obtaining the OPI with greater accuracy.

Item Type:Thesis (MTech)
Uncontrolled Keywords:Power system security, contingency, outages, Performance index, Artificial Neural Network, Fuzzy Logic.
Subjects:Engineering and Technology > Electrical Engineering > Power Systems
Divisions: Engineering and Technology > Department of Electrical Engineering
ID Code:6134
Deposited By:Hemanta Biswal
Deposited On:27 Aug 2014 17:18
Last Modified:27 Aug 2014 17:18
Supervisor(s):Mohanty, S

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