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Algoritmo de optimización por senos y cosenos aplicado al problema de estimación paramétrica en transformadores monofásicos considerando medidas de tensión y corriente
Sine-cosine optimization approach applied to the parametric estimation in single-phase transformers by considering voltage and current measures
DOI:
https://doi.org/10.15446/dyna.v88n219.93670Palabras clave:
estimación paramétrica en transformadores monofásicos;, medidas de voltaje y corriente;, programación no lineal;, algoritmo de senos y cosenos;, optimización metaheurística. (es)parametric estimation in single-phase transformers;, nonlinear programming model;, sine-cosine algorithm;, metaheuristic optimization. (en)
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En este artículo un enfoque de optimización combinatorial para la estimación paramétrica en transformadores monofásicos considerando medidas de tensión y corriente es propuesto. El problema de estimación paramétrica es formulado mediante un modelo de programación no lineal. Este modelo matemático se desarrolla mediante la aplicación de las leyes de Kirchhoff al modelo equivalente del transformador monofásico. Para resolver este modelo se emplea el algoritmo de senos y cosenos, el cual corresponde a una técnica de optimización combinatorial de dominio continuo, la cual pertenece a la familia de las técnicas de optimización metaheurística que tiene la habilidad de encontrar soluciones de buena calidad con mínimo esfuerzo computacional, siendo fácilmente implementable en cualquier lenguaje de programación. Los resultados numéricos muestran que el modelo de estimación paramétrica no lineal que se propone representa adecuadamente el comportamiento del transformador ante diferentes escenarios de demanda. Todas las simulaciones se desarrollan en el ambiente de programación de MATLAB y son comparadas con la implementación del modelo no lineal en el software de optimización GAMS.
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.
Referencias
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