An economical solution to the quality of service problems of electricity supply

This article proposes a methodology for the construction of hybrid models for the location of failures in electric power distribution systems, which will allow distribution companies to improve their quality indices regarding the continuity of energy supply (DES and FES indexes ). The hybrid model proposed within the methodology is made up of a knowledge-based technique (LAMDA technique) and another based on the model (Ratan Das algorithm). The LAMDA technique is a technique based on artificial intelligence that inherits characteristics of diffuse logic and neural networks. The Ratan Das algorithm is a fault location algorithm that estimates the location of the fault from the voltage and current phasors at the same time and other electrical parameters of the distribution system. The novelty of the methodology is that with the implementation of the hybrid model, the precision in the estimation of the fault location is improved, because the multiple estimation of the location algorithm is significantly reduced by the presence of the technique based on the knowledge. Finally, the results obtained from tests performed with a distribution circuit of 24 kV and approximately 60 km in length are presented.

• Autores: Barrera Núñez, Víctor; Mora Flórez, Juan José; Carrillo, Gilberto; Ordóñez Plata, Gabriel
• Fecha de publicación: 2006
• Institución: Universidad EAFIT
• Repositorio: Repositorio EAFIT
• Idioma: spa
• OAI Identifier: oai:repository.eafit.edu.co:10784/14555
• Acceso en línea: http://hdl.handle.net/10784/14555
• Palabra clave: Power Quality; Multivariable Classification; Continuity Of Electricity Supply; Quality Indicators; Artificial Intelligence; Fault Location; Lamda Technique; Calidad De Potencia; Clasificación Multivariable; Continuidad Del Suministro De Energía Eléctrica; Indicadores De Calidad; Inteligencia Artificial; Localización De Fallas; Técnica Lamda
• License: Acceso abierto