Metodología para la estimación de curva de carga diaria para un circuito de media tensión (13.2 kv) a partir de técnicas inteligentes
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Álvarez Barreto, Juan Carlos
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Una curva de demanda diaria confiable contiene información valiosa para realizar distintos análisis, como por ejemplo el cálculo de pérdidas técnicas de energía a partir de flujos de potencia horarios. El propósito de este documento es el de presentar un método para la estimación de una curva de demanda confiable, que pueda ser empleado por los operadores de red para uso en el análisis de sus redes. El método consiste en varias etapas secuenciales, preproceso, limpieza, estimación y ajuste, utilizando MATLAB como herramienta informática con técnicas de minería de datos para la agrupación y depuración de datos. La curva final se ajusta contrastándola con la energía medida y finalmente suavizada para mejorar los resultados
Abstract : A curve of reliable daily demand contains valuable information to perform analysis, such as the calculation of energy technical losses from hourly power flows. The purpose of this document is to present a method to estimate a reliable demand curve that can be used by grid operators in the analysis of their networks. The method consists of several sequential stages: pre-processing, data cleaning, estimation and adjustment. It uses MATLAB as a software tool with data mining techniques for grouping and data cleansing. The final curve is adjusted by comparing the measured energy curve to the obtained smoothed curve to improve results
Abstract : A curve of reliable daily demand contains valuable information to perform analysis, such as the calculation of energy technical losses from hourly power flows. The purpose of this document is to present a method to estimate a reliable demand curve that can be used by grid operators in the analysis of their networks. The method consists of several sequential stages: pre-processing, data cleaning, estimation and adjustment. It uses MATLAB as a software tool with data mining techniques for grouping and data cleansing. The final curve is adjusted by comparing the measured energy curve to the obtained smoothed curve to improve results