Normalized Radial Basis Function Network with Hierarchical Deterministic Annealing for Electricity Price Zone Forecasting

In this paper, a new method is proposed for electricity price zone forecasting. The proposed method employs the normalized radial basis function network that modifies the radial basis function network by the normalization technique, uses hierarchical deterministic annealing clustering to determine the center of NRBFN. Also, clipping is used for output of NRBFN to simplify the problem whether one-step-ahead price zone exceeds a threshold value. Furthermore, a set of threshold are prepared to construct a binary tree that classifies the price zone into clusters. The proposed method is successfully applied to real data of ISO New England.