A novel PSO‐based technique for optimal design of protective current transformers

A novel PSO‐based technique for optimal design of protective current transformers Purpose – The purpose of this paper is to present a new approach for the optimal design of protective current transformers (CTs). The proposed technique is applied to the design of typical CTs and results are compared with traditional CT design method and genetic algorithm optimization algorithm. Design/methodology/approach – The aim of CT design is to make current measurements more accurately, particularly for the high fault currents which arise in short circuits, and more efficient CT in terms of both size and cost. The present work formulates these objectives as an optimization problem to be solved by particle swarm optimization. Findings – Simulation results demonstrate the effectiveness of this technique in optimizing the CT design parameters. The designed CTs have smaller measurement errors compared to standard values and respond well to high fault currents. Manufacturing costs have also been reduced. Originality/value – In addition to improved efficiency, the benefits of this method are its treatment of CT design in terms of an equivalent circuit and design parameters. The proposed algorithm also extends the linear operation area of the CT and guarantees its good response to high fault currents that may occur in power systems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering Emerald Publishing

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Publisher
Emerald Publishing
Copyright
Copyright © 2011 Emerald Group Publishing Limited. All rights reserved.
ISSN
0332-1649
DOI
10.1108/03321641111101041
Publisher site
See Article on Publisher Site

Abstract

Purpose – The purpose of this paper is to present a new approach for the optimal design of protective current transformers (CTs). The proposed technique is applied to the design of typical CTs and results are compared with traditional CT design method and genetic algorithm optimization algorithm. Design/methodology/approach – The aim of CT design is to make current measurements more accurately, particularly for the high fault currents which arise in short circuits, and more efficient CT in terms of both size and cost. The present work formulates these objectives as an optimization problem to be solved by particle swarm optimization. Findings – Simulation results demonstrate the effectiveness of this technique in optimizing the CT design parameters. The designed CTs have smaller measurement errors compared to standard values and respond well to high fault currents. Manufacturing costs have also been reduced. Originality/value – In addition to improved efficiency, the benefits of this method are its treatment of CT design in terms of an equivalent circuit and design parameters. The proposed algorithm also extends the linear operation area of the CT and guarantees its good response to high fault currents that may occur in power systems.

Journal

COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic EngineeringEmerald Publishing

Published: Mar 8, 2011

Keywords: Transformers; Optimization techniques; Programming and algorithm theory; Electric current; Phase (electric); Systems and control theory

References

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