Back to Search
Start Over
Estimation of the Equivalent Circuit Parameters in Transformers Using Evolutionary Algorithms
- Source :
- Mathematical and Computational Applications, Vol 28, Iss 2, p 36 (2023)
- Publication Year :
- 2023
- Publisher :
- MDPI AG, 2023.
-
Abstract
- The conventional methods of parameter estimation in transformers, such as the open-circuit and short-circuit tests, are not always available, especially when the transformer is already in operation and its disconnection is impossible. Therefore, alternative (non-interruptive) methods of parameter estimation have become of great importance. In this work, no-interruption, transformer equivalent circuit parameter estimation is presented using the following metaheuristic optimization methods: the genetic algorithm (GA), particle swarm optimization (PSO) and the gravitational search algorithm (GSA). These algorithms provide a maximum average error of 12%, which is twice as better as results found in the literature for estimation of the equivalent circuit parameters in transformers at a frequency of 50 Hz. This demonstrates that the proposed GA, PSO and GSA metaheuristic optimization methods can be applied to estimate the equivalent circuit parameters of single-phase distribution and power transformers with a reasonable degree of accuracy.
Details
- Language :
- English
- ISSN :
- 22978747, 1300686X, and 48178896
- Volume :
- 28
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- Mathematical and Computational Applications
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.48178896c2514446adc47bbd86c3b894
- Document Type :
- article
- Full Text :
- https://doi.org/10.3390/mca28020036