Monitoring Short Term Load Forecasting (STLF) with Graphical User Interface

Intan Azmira , Wan Abd. Razak and Mohd Shahrieel , Mohd Aras and Alias , Khamis and Junainah , Sardi and Mohd Firdaus, Baharuddin (2011) Monitoring Short Term Load Forecasting (STLF) with Graphical User Interface. [Show/Exhibition]

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Abstract

This project will focus on development of algorithms and graphical-user-interface (GUI) of short-term load forecasting with artificial neural network using MATLAB software. Two algorithms will be used such as Multilayer Perceptron (MLP) and Back Propagation (BP) method to forecast the future load in Peninsular Malaysia within 24 hours for a day or a week ahead with minimum forecasting error. This project demonstrates the development of short term load forecasting algorithms and its interface using the MLP and BP artificial neural network model for power distribution systems. The load data is provided by the utility company in Malaysia. A graphical user interface (GUI) would be the output of an easier interface program for customers’ usage. Thus, this proposed project would involve the implementation of MATLAB software to come out with user-friendly short term load forecasting software through suitable algorithms and GUI. The GUI enables forecaster to forecast load in a quick way by just selecting day and time with minimum forecasting error.

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