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Application of Neural Networks for Short Term Load Forecasting in Power System of North Macedonia

Air temperature, type of the day and humidity are factors that have significant impact on electricity consumption and power system load on a short term. In the paper, neural networks are successfully applied for load forecasting on a short term in a power system of Republic of North Macedonia. The training of neural network is performed on real input data. The forecast is obtained on the basis on the trained network and learned relationship through training process.