%0 Journal Article
%T Artificial Neural Network-based Approach for Short-term Electricity Price Forecasting
%A Mfonobong A. Umoren
%A Umoh T. Umoh
%A and Ye-Obong N. Udoakah
%J GSTF Journal of Engineering Technology
%P 98-103
%@ 2251-371X
%D 2015
%R 10.5176/2251-3701_3.3.148
%X Electricity price forecasting has become an integral part of power system operation and control. This paper presents an artificial neural network (ANN), based approach for estimating short-term wholesale electricity price using past price and demand data. In other to obtain accurate model, several combination of input parameters was considered. 70% of the data sample was used for training, 15% for validation and 15% for testing. The ANN model was trained in MATLAB using Levenberg-Marquardt back propagation algorithm for forecasting the next 24 hours electricity price. The accuracy of the model was measured using Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE).
%K Artificial Network
%K Electricity Market
%K LevenbergMarquardt Algorithm
%K Price forecasting
%U http://dl6.globalstf.org/index.php/jet/article/view/1488/1504