Electric Load Forecasting Model for the State of Bahrain Network

The present paper presents a class of week series forecasting manner. This class, employed in the extent of long-term electric load forecasting, is based on Fuzzy Inference Clustering (FIC) method along with ANN. The FIC is followed to arrange the operating week correctly. In the proposed algorithm, the FIC was used to evaluate the classes. The power of the proposed architecture is shown by one week in advance of Bahrain power system grid. The unfamiliar use of information obtaining from the arrangement stage permits the procedure used in finding a relevant enhancement of the forecast correctness for irregular load situations. The employed fuzzy clustering algorithm is useful also for linguistic modeling of an electric power demand used for higher hierarchy decision system. The algorithm is explained in detail and verified through a numerical example of state of Bahrain network.