Adaptive model for a variable load in a distribution network using a neuro-fuzzy system

Abstract

Distributed generation systems are a suitable alternative for the rational use of energy. One of important aspect in these systems corresponds to the modeling of the transmission system and its loads which are usually variable. Neuro-fuzzy systems are an alternative for modeling and control of complex systems, allowing the adaptability of their parameters using data. This article shows the modeling of a node in a distribution system considering in adaptive way the load variability during a time interval.