Performance Analysis of Loop Frame of Reference over Bus Frame of Reference

Performance analysis of loop frame of reference over bus frame of reference is carried out in this study. Impedance matrices for fault current calculations are found out in bus and loop frames of references. In bus frame of reference, bus impedance matrix Zbus is formulated by inverting bus admittance matrix Ybus. In loop frame of reference, loop impedance matrix Zloop is calculated using graph theory. These methods are compared and verified with the standard IEEE 14 bus system. The results have proved that loop frame of reference can outperform the bus frame of reference with less computation time and memory. This performance analysis can be applied for fault analysis of larger power system networks.

[1]  A. Brameller,et al.  General fault analysis using phase frame of reference , 1974 .

[2]  M. Salama,et al.  Distribution system reconfiguration for loss reduction: an algorithm based on network partitioning theory , 1995, Proceedings of Power Industry Computer Applications Conference.

[3]  Nikos D. Hatziargyriou,et al.  Optimal operation of distribution networks , 1996 .

[4]  Northwoods Pkwy.  Distribution Network Reconfiguration: Single Loop Optimization , 1996 .

[5]  H Ghoujehbaklou,et al.  A NEW ALGORITHM FOR OPTIMUM VOLTAGE AND REACTIVE POWER CONTROL FOR MINIMIZING TRANSMISSION LINES LOSSES , 2001 .

[6]  M. M. Morcos,et al.  Artificial Intelligence and Advanced Mathematical Tools for Power Quality Applications: A Survey , 2001, IEEE Power Engineering Review.

[7]  S. Sivanagaraju,et al.  Enhancing Voltage Stability of Radial Distribution Systems by Network Reconfiguration , 2005 .

[8]  Julio Barros,et al.  Automatic Detection and Analysis of Voltage Events in Power Systems , 2006, IEEE Transactions on Instrumentation and Measurement.

[9]  Chika O. Nwankpa,et al.  Voltage Stability Toolbox for Power System Education and Research , 2006, IEEE Transactions on Education.

[10]  M. M. Abu-Elnaga,et al.  Voltage Stability Assessment of Multi-Machine Power Systems Using Energy Function and Neural Networks Techniques , 2006 .

[11]  Chun-xia Dou,et al.  A WAMS/PMU-based fault location technique , 2007 .

[12]  Yilu Liu,et al.  Rough set and fuzzy wavelet neural network integrated with least square weighted fusion algorithm based fault diagnosis research for power transformers , 2008 .

[13]  Tianshu Bi,et al.  A novel hybrid state estimator for including synchronized phasor measurements , 2008 .

[14]  Chun-xia Dou,et al.  Fault location using synchronized sequence measurements , 2008 .

[15]  J S Savier,et al.  A MULTI-OBJECTIVE METHOD FOR NETWORK RECONFIGURATION (TECHNICAL NOTE) , 2009 .

[16]  Zengping Wang,et al.  Recent Research Progress in Fault Analysis of Complex Electric Power Systems , 2010 .

[17]  S. Vetrivel,et al.  APPLICATIONS OF GRAPH THEORY IN COMPUTER SCIENCE AN OVERVIEW , 2010 .

[18]  Zengping Wang,et al.  PCA Fault Feature Extraction in Complex Electric Power Systems , 2010 .

[19]  Jinfang Zhang,et al.  Fault localization in electrical power systems: A pattern recognition approach , 2011 .

[20]  Zengping Wang,et al.  A Novel Fault Identification Using WAMS/PMU , 2012 .

[21]  T. Oepomo.  Applied Graph Theory and Topology for 3 Phase Power System Under Faulted Studies , 2014 .