Abstract
Abstract Two algorithms for short-term electricity demand forecasting in the regional electricity distribution network are presented. Several approaches - feedforward neural network, adaptive modelling and fuzzy modelling - are applied to the forecast. Two different models are designed. A one hour forecasting is based on the General Regression Neural Network (GRNN) model and Principle Component Analysis. The multi-model with adaptive features and fuzzy reasoning is used for a longer-term forecast.
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