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Estimation of electrical transformer parameters with reference to saturation behavior using artificial hummingbird optimizer.
Kotb, Mohamed F; El-Fergany, Attia A; Gouda, Eid A.
Affiliation
  • Kotb MF; Department of Electrical Engineering, Faculty of Engineering, Mansoura University, Mansoura, Egypt. mohamadfawzi@gmail.com.
  • El-Fergany AA; Department of Electric Power and Machines, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt.
  • Gouda EA; Department of Electrical Engineering, Faculty of Engineering, Mansoura University, Mansoura, Egypt.
Sci Rep ; 12(1): 19623, 2022 Nov 15.
Article in En | MEDLINE | ID: mdl-36380067
ABSTRACT
This paper offers an efficient tool to define the unknown parameters of electrical transformers. The proposed methodology is developed based on artificial hummingbird optimizer (AHO) to generate the best values of the transformer's unknown parameters. At initial stage, the parameters' extraction of the transformer electrical equivalent is adapted as an optimization function along with the associated operating inequality constraints. In which, the sum of absolute errors (SAEs) among many variables from nameplate data of transformers is decided to be minimized. Two test cases of 4 kVA and 15 kVA transformers ratings are demonstrated to indicate the ability of the AHO compared to other recent challenging optimizers. The proposed AHO achieves the lowest SAE's value than other competing algorithms. At advanced stage of this effort, the capture of percentage of loading to achieve maximum efficiency is ascertained. At later stage, the performance of transformers utilizing the extracted parameters cropped by the AHO to investigate the principal behavior at energization of these transformer units is made. At the end, it can be confirmed that the AHO produces best values of transformer parameters which help much in achieving accurate simulations for steady-state and inrush behaviors.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Egypt

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sci Rep Year: 2022 Document type: Article Affiliation country: Egypt