Model Order Reduction based on meta-heuristic optimization methods

Journal Title: International Research Journal of Applied and Basic Sciences - Year 2013, Vol 7, Issue 1

Abstract

Determining the stability region and recognizing the limits that exist in a large scale system such as in a power network are very significant. According to daily changes in these systems, such as changing power plan or network structure, it is necessary to use a dynamic method with instantaneous measurement for modeling. On the other hand, one of the biggest challenges in system identification is order selection. Due to the large number of parameters and daily changes in such system, system order permanently changes. In this paper a new method has been suggested. In this method we use metaheuristic algorithms, such as SA and SFL that are merged with other order selection methods to obtain more accurate results. Also, we use ERA/DC and Prony for extracting dynamic model. These Methods have been implemented on extracted data from simulated Iran power network Model in DIgSILENT software.

Authors and Affiliations

Mehdi Safaeian| Islamic Azad University, Hidaj Branch, Iran, email: m.safaeian@gmail.com

Keywords

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  • EP ID EP6345
  • DOI -
  • Views 319
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How To Cite

Mehdi Safaeian (2013). Model Order Reduction based on meta-heuristic optimization methods. International Research Journal of Applied and Basic Sciences, 7(1), 25-31. https://europub.co.uk/articles/-A-6345