Short Term Load Forecasting With Perceptron Artificial Neural Network

Khairul Anuar, Mohd Padzil (2010) Short Term Load Forecasting With Perceptron Artificial Neural Network. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Short term load forecasting is important in predicting and analysis power distribution for a short period of time in many places. This project paper present the use of perceptron artificial neural network model for short term load forecasting in power distribution systems. Thus, this proposed project involves with case study and Matlab software implementation to come out with a model that can forecast future load for a week ahead. The expecting load forecast is to get minimum forecasting error of at least 1.5 percent. Furthermore, the suitability of the proposed approach is illustrated through an application to real load shapes provided utility of Malaysia. The data represent half hourly load data for 6 weeks in Peninsular Malaysia.

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