ABSTRACT
Artificial neural networks (ANN) are systems inspired by research into how the brain works. An ANN consists of a collection of arithmetic computing units connected together in a network of interconnected layers. The ANN learns by adjusting or adapting the connection weights through comparing the output of the ANN to the expected output. Once the ANN is trained, the extracted knowledge from the process resides in the resulting connection weights in a distributed manner. The chapter describes the third generation of an ANN hourly load forecaster known as Artificial Neural Network Short-Term Load Forecaster. Application of ANN technology to electricity price forecasting is relatively new and there are few published studies on the subject. Holidays and special days pose a challenge to any load forecasting program since the load of these days can be quite different from a regular workday. The holiday peak forecasting algorithm uses a novel weighted interpolation scheme.
