Application of Evolutionary Algorithm for Optimal Directional Overcurrent Relay Coordination

In this paper, two Evolutionary Algorithms (EAs) i.e., an improved Genetic Algorithms (GAs) and Population Based Incremental Learning (PBIL) algorithm are applied for optimal coordination of directional overcurrent relays in an interconnected power system network. The problem of coordinating directional overcurrent relays is formulated as an optimization problem that is solved via the improved GAs and PBIL. The simulation results obtained using the improved GAs are compared with those obtained using PBIL. The results show that the improved GA proposed in this paper performs better than PBIL.

[1]  J. Sadeh,et al.  Considering Different Network Topologies in Optimal Overcurrent Relay Coordination Using a Hybrid GA , 2009, IEEE Transactions on Power Delivery.

[2]  Ajith Abraham,et al.  New mutation schemes for differential evolution algorithm and their application to the optimization of directional over-current relay settings , 2010, Appl. Math. Comput..

[3]  Komla A. Folly.  Robust Controller Design Based on a Combination of Genetic Algorithms and Competitive Learning , 2007, 2007 International Joint Conference on Neural Networks.

[4]  K. K. Li,et al.  Application of genetic algorithm to overcurrent relay grading coordination , 1997 .

[5]  F. Kavehnia,et al.  Optimal Coordination of Directional Over Current Relays in Power System Using Genetic Algorithm , 2006, Proceedings of the 41st International Universities Power Engineering Conference.

[6]  H. Askarian Abyaneh,et al.  Optimal Overcurrent relays coordination using genetic algorithm , 2008, 2008 11th International Conference on Optimization of Electrical and Electronic Equipment.

[7]  A. J. Urdaneta,et al.  Optimal coordination of directional overcurrent relays in interconnected power systems , 1988 .

[8]  Prashant P. Bedekar,et al.  Optimum coordination of overcurrent relay timing using continuous genetic algorithm , 2011, Expert Syst. Appl..

[9]  Carlos Artemio Coello-Coello,et al.  Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: a survey of the state of the art , 2002 .

[10]  H. Y. Tsien,et al.  An Automatic Digital Computer Program for Setting Transmission Line Directional Overcurrent Relays , 1964 .

[11]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[12]  Kusum Deep,et al.  Optimal coordination of over-current relays using modified differential evolution algorithms , 2010, Eng. Appl. Artif. Intell..

[13]  Hossein Askarian Abyaneh,et al.  A new comprehensive genetic algorithm method for optimal overcurrent relays coordination , 2008 .

[14]  K.K. Li,et al.  Intelligent method for protection coordination , 2004, 2004 IEEE International Conference on Electric Utility Deregulation, Restructuring and Power Technologies. Proceedings.

[15]  C. L. Wagner,et al.  Digital Computer Protective Device Co-ordination Program I-General Program Description , 1964 .

[16]  Randy L. Haupt,et al.  Practical Genetic Algorithms , 1998 .

[17]  Komla A. Folly,et al.  Performance evaluation of power system stabilizers based on Population-Based Incremental Learning (PBIL) algorithm , 2011 .

[18]  K. R. Krishnanand,et al.  Adaptive differential evolution algorithm for solving non-linear coordination problem of directional overcurrent relays , 2013 .

[19]  R. Thangaraj,et al.  Overcurrent relay coordination by Differential Evolution algorithm , 2012, 2012 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES).

[20]  Komla A. Folly,et al.  A Real-Time Implementation of a PBIL Based Stabilizing Controller for Synchronous Generator , 2009, 2009 IEEE Industry Applications Society Annual Meeting.

[21]  Hari Om Gupta,et al.  Time-Overcurrent Relay Coordination: A Review , 2005 .

[22]  Shumeet Baluja,et al.  A Method for Integrating Genetic Search Based Function Optimization and Competitive Learning , 1994 .

[23]  Komla A. Folly.  Population-Based Incremental with Adaptive Learning Rate Strategy , 2012, ICSI.

[24]  Ismail Musirin,et al.  Optimal Overcurrent Relay Coordination: A Review , 2013 .

[25]  Ieee Standards Board.  IEEE recommended practice for protection and coordination of industrial and commercial power systems : an American national standard , 1986 .

[26]  Paul M. Anderson.  Power System Protection , 1998 .

[27]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[28]  K. K. Li,et al.  Overcurrent relay coordination by evolutionary programming , 2000 .

[29]  K.A. Folly.  Design of power system stabilizer: a comparison between genetic algorithms (GAs) and population-based incremental learning (PBIL) , 2006, 2006 IEEE Power Engineering Society General Meeting.