IDENTIFICACIÓN EFICIENTE DE ERRORES EN ESTIMACIÓN DE ESTADO USANDO UN ALGORITMO GENÉTICO ESPECIALIZADO (EFFICIENT IDENTIFICATION OF ERRORS IN STATE ESTIMATION THROUGH A SPECIALIZED GENETIC ALGORITHM)
IDENTIFICACIÓN EFICIENTE DE ERRORES EN ESTIMACIÓN DE ESTADO USANDO UN ALGORITMO GENÉTICO ESPECIALIZADO (EFFICIENT IDENTIFICATION OF ERRORS IN STATE ESTIMATION THROUGH A SPECIALIZED GENETIC ALGORITHM)


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En este artículo se presenta un método para resolver el problema de estimación de estado en sistemas eléctricos usando optimización combinatoria. Su objetivo es el estudio de mediciones con errores de difícil detección, que afectan el desempeño y calidad de los resultados cuando se emplea un estimador de estado clásico. Dada su complejidad matemática, se deducen indicadores de sensibilidad de la teoría de puntos de apalancamiento que se usan en el algoritmo de optimización de Chu-Beasley, con el fin de disminuir el esfuerzo computacional y mejorar la calidad de los resultados. El método propuesto se valida en un sistema IEEE de 30 nodos
Abstract: In this paper a method to solve the state estimation problem in electric systems applying combinatorial optimization is presented. Its objective is the study of measures with difficult detection errors, which affect the performance and quality of the results when a classic state estimator is used. Due to the mathematical complexity, sensibility indicators are deduced from the theory of leverage points used in the Chu-Beasley optimization algorithm with the purpose of reducing the computational effort and enhance the quality of the results. The proposed method is validated in a 30-node IEEE system.
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