Tai, Hein Fong creator text theses my Kuantan, Pahang UMP 2009 monographic eng

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xiv, 112 p. : ill. (some col.) ; 30 cm. + 1 computer disc Load forecasting is very essential to the operation of electricity companies. It enhances the energy-efficient and reliable operation of a power system. This is a case study of short-term load forecasting using Artificial Neural Networks (ANNs). This load forecasting program gives load forecasts half an hour in advance. Historical load data obtained from the electricity generation company will be use. The main stages are the pre-processing of the data sets, network training, and forecasting. The inputs used for the neural network are one set of historical load demand data and five sets of temperature data. The neural network used has 3 layers: an input, a hidden, and an output layer. The input layer has 5 neurons, the number of hidden layer neurons can be varied for the different performance of the network, while the output layer has a single neuron. specialized Tai Hein Fong Project paper (Bachelor of Electrical Engineering (Power System)) -- Universiti Malaysia Pahang - 2009 Electric power-plants Load Forecasting Electric power systems THE0006681(Local) UMP 110804 20251114204452.0 vtls000055190