Abstract:
This thesis is a study of short-term electric power forecasting in the Nigerian power
system using artificial neural network model. The model is created in the form of a
simulation program written with MATLAB tool. The model, a multilayer timedelayed
feed-forward artificial neural network trained with error back propagation
algorithm, was made to study the pre-historical load pattern of a typical Nigerian
power system in a supervised training manner. After presenting the model with a
reasonable number of training samples, the model could forecast correctly electric
power supply in the Nigerian power system 24 hours in advance. An absolute mean
error of 4.27% was obtained when the trained neural network model was tested on
one week, daily hourly load data of a typical Nigerian power station. This result
demonstrates that ANN is a powerful tool for load forecastin
