Optimal coordination of directional over current relays using a modified real coded genetic algorithm: A comparative study. (November 2016)

• Record Type: Journal Article
• Authors: Thakur, Manoj; Kumar, Anand
• Is Part Of: International journal of electrical power & energy systems. Volume 82(2016:Nov.)
• Page Start: 484
• Page End: 495
• Publication Date: 2016-11
• Subjects: Overcurrent relay -- Power system protection -- Optimization -- Real coded genetic algorithm -- Constraint handling; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2016.03.036
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: This paper applies BEX–PM, a modified GA based algorithm, for relay coordination. Four standard IEEE 3-bus, 4-bus, 6-bus and 14-bus networks are considered as test models. Performance of the BEX–PM is compared with 13 other algorithms applied to solve the same networks. Results obtained by BEX–PM outperforms all other considered algorithms. Abstract: In a large distribution network, the coordination of relays is a highly constrained optimization problem with the objective to minimize the overall operating time of each primary relay. For proper functioning of the power system with distributed power generating stations, appropriate coordination of protection devices is crucial. The present work incorporates bounded exponential crossover and power mutation (BEX–PM) into Real Coded Genetic Algorithm (RCGA) in order to find optimal settings for the Directional Overcurrent Relays (DOCRs). Optimal settings are obtained to minimize the overall action time of all the primary relays as well as to get rid of miscoordination among the backup/primary relay pairs. Another objective of the work is to maintain the difference of response time of backup relay and corresponding primary relay to possible minimum. Results obtained are compared with various approaches available in the literature. The results of this work evidences the compatibility of the proposed strategy in solving complex real-world optimization problems and applicability of the obtained results.