Estimation of the Equivalent Circuit Parameters in Transformers Using Evolutionary Algorithms
| Autor: | Hector Ascencion-Mestiza, Serguei Maximov, Efrén Mezura-Montes, Juan Carlos Olivares-Galvan, Rodrigo Ocon-Valdez, Rafael Escarela-Perez |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Mathematical and Computational Applications, Vol 28, Iss 2, p 36 (2023) |
| Druh dokumentu: | article |
| ISSN: | 2297-8747 1300-686X 48178896 |
| DOI: | 10.3390/mca28020036 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
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