Electricity prices forecasting using ANN Hybrid with Invasive Weed Optimization (IWO)

Electricity prices forecasting is an important tool for power generating company to make investment decision, engage with long-term contracts, bidding in short-term market and other strategic actions. It is also a useful tool for electricity consumers to manage their demand consumption. In this paper an Artificial Neural Network (ANN) Hybrid with Invasive Weed Optimization (IWO) is introduced to forecast the electricity prices in the environment of restructured power market such as Australian Market. The ANN model uses the conventional back propagation technique, but the number of neuron nodes, learning rate and momentum constant are optimally determined using the IWO technique. Result shows that the ANN-IWO technique gives a better performance in term of forecasting error than the ANN technique alone.