| Issue |
E3S Web Conf.
Volume 336, 2022
The International Conference on Energy and Green Computing (ICEGC’2021)
|
|
|---|---|---|
| Article Number | 00052 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/e3sconf/202233600052 | |
| Published online | 17 January 2022 | |
Parameters Identification of Synchronous Machine Based on Particale Swarm Optimization
1 LAS Laboratory, Electrical Engineering Department, Setif 1 University, Setif, Algeria.
2 LSI Laboratory, Electronic Department, Setif 1 University, Setif, Algeria.
* e-mail: bendaoud.elrachid@gmail.com
** e-mail: hradjeai@yahoo.fr
*** e-mail: botalbioussama@gmail.com
This paper, deals with a meta-heuristic method, the Particle Swarm Optimization (PSO), for operational parameters identification of synchronous machine. The considered method consists of minimizing quadratic criterion that represents the difference between simulated model at standstill frequency response output and those computed from the model to be identified. The obtained results by simulation show that the method based on particle swarm optimization is efficient in terms of convergence speed and gives optimal solution.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.