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Short Term Load Forecasting With Artificial Neural Network

Intan Azmira, Abdul Razak and Mohd Shahrieel, Mohd Aras and Alias, Khamis and Aziah , Khamis and Elia Erwani, Hassan (2010) Short Term Load Forecasting With Artificial Neural Network. Project Report. UTeM, Melaka, Malaysia. (Submitted)

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Abstract

Load forecasting has become one of the major areas of research in electrical engineering in recent years. Several electric companies are now forecasting load power based on conventional method. However, since the relationship between load power and factor influencing load power is nonlinear, it is difficult to identify its nonlinearity by using conventional method. For this project, it involves short term load forecasting (STLF) with feed forward neural network algorithm. Artificial Neural Network (ANN) has been proved as a powerful alternative for STLF that it is not relying on human experience. This project deals with case study and simulation using Neural Network in MA TLAB software to forecast load in Peninsular Malaysia. The load data is taken for half hourly load because the aim is to get the minimum error about less or equals to 1.5%.

Item Type: Monograph (Project Report)
Uncontrolled Keywords: Electric power-plants -- Load -- Forecasting, Electric power consumption -- Forecasting, Electric utilities -- Planning
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Library > Projek Jangka Panjang / Pendek > FKE
Depositing User: Nor Aini Md. Jali
Date Deposited: 11 Jul 2014 01:49
Last Modified: 28 May 2015 04:26
URI: http://eprints.utem.edu.my/id/eprint/12612

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