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Mathematical Problems in Engineering
Volume 2017, Article ID 5274517, 14 pages
https://doi.org/10.1155/2017/5274517
Research Article

Implementation of SoC Based Real-Time Electromagnetic Transient Simulator

1Cinvestav, Unidad Guadalajara, Del Bosque Av. 1145, El Bajío, 45019 Zapopan, JAL, Mexico
2Cátedras Conacyt-Cinvestav, Unidad Guadalajara, Del Bosque Av. 1145, El Bajío, 45019 Zapopan, JAL, Mexico

Correspondence should be addressed to S. Ortega-Cisneros; xm.vatsevnic.ldg@agetros

Received 23 September 2016; Revised 23 January 2017; Accepted 29 January 2017; Published 8 March 2017

Academic Editor: Paolo Boscariol

Copyright © 2017 I. Herrera-Leandro et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Real-time electromagnetic transient simulators are important tools in the design stage of new control and protection systems for power systems. Real-time simulators are used to test and stress new devices under similar conditions that the device will deal with in a real network with the purpose of finding errors and bugs in the design. The computation of an electromagnetic transient is complex and computationally demanding, due to features such as the speed of the phenomenon, the size of the network, and the presence of time variant and nonlinear elements in the network. In this work, the development of a SoC based real-time and also offline electromagnetic transient simulator is presented. In the design, the required performance is met from two sides, (a) using a technique to split the power system into smaller subsystems, which allows parallelizing the algorithm, and (b) with specialized and parallel hardware designed to boost the solution flow. The results of this work have shown that for the proposed case studies, based on a balanced distribution of the node of subsystems, the proposed approach has decreased the total simulation time by up to 99 times compared with the classical approach running on a single high performance 32-bit embedded processor ARM-Cortex A9.