Sine-cosine optimization approach applied to the parametric estimation in single-phase transformers by considering voltage and current measures

In this article, a combinatorial optimization approach for estimating the electrical parameters in single-phase distribution transformers by considering voltage and current measures is presented. A nonlinear programming model was formulated to represent the parametric estimation problem. This mathematical optimization model was developed by applying Kirchhoff’s laws to the equivalent electric circuit of the transformer. To solve the NLP model is employed the sine-cosine algorithm, which corresponds to a combinatorial optimization methodology from the family of metaheuristics that has the ability for finding good solutions with minimum computational requirements, easily implementable at any programming language. Numerical results show that the parametric estimation in the transformers using the proposed NLP model represents the electrical behavior of these devices adequately, considering different load scenarios. All the simulations were carried out using MATLAB software and compared with the GAMS optimization package.

• Autores: Bocanegra, Sara Yulieth; Montoya, Oscar Danilo; Molina-Cabrera, Alexander
• Fecha de publicación: 2021
• Institución: Universidad Tecnológica de Bolívar
• Repositorio: Repositorio Institucional UTB
• Idioma: eng
• OAI Identifier: oai:repositorio.utb.edu.co:20.500.12585/12178
• Acceso en línea: https://hdl.handle.net/20.500.12585/12178
• Palabra clave: Metaheuristic optimization; Nonlinear programming model; Parametric estimation in single-phase transformers; Sine-cosine algorithm; Voltage and current measures
• Rights: openAccess
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/