Hybrid PSO-Complex Algorithm Based Parameter Identification for a Composite Load Model
- Authors
- Del Castillo, Manuelito Y., Jr.; Song, Hwachang; Lee, Byongjun
- Issue Date
- 5월-2013
- Publisher
- SPRINGER SINGAPORE PTE LTD
- Keywords
- Composite load model; Complex method; Hybrid search; Parameter identification; Particle swarm optimization
- Citation
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.8, no.3, pp.464 - 471
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY
- Volume
- 8
- Number
- 3
- Start Page
- 464
- End Page
- 471
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/103342
- DOI
- 10.5370/JEET.2013.8.3.464
- ISSN
- 1975-0102
- Abstract
- This paper proposes a hybrid searching algorithm based on parameter identification for power system load models. Hybrid searching was performed by the combination of particle swarm optimization (PSO) and a complex method, which enhances the convergence of solutions closer to minima and takes advantage of global searching with PSO. In this paper, the load model of interest is composed of a ZIP model and a third-order model for induction motors for stability analysis, and parameter sets are obtained that best-fit the output measurement data using the hybrid search. The origin of the hybrid method is to further apply the complex method as a local search for finding better solutions using the selected particles from the performed PSO procedure.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of Engineering > School of Electrical Engineering > 1. Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.