Using artificial neural networks for long term peak load forecasting "a case study in Vientiane capital of Lao PDR"

Name: Santisouk Phimphachanh

Organization : King Mongkut's University of Technology Thonburi. Faculty of Engineering. Electrical and Information Engineering

keyword: Long Term Peak Load Forecasting

Abstract: Long Term Peak Load Forecasting (LTPLF) plays an important role in electrical powersystems in terms of policy planning and budget allocation. The planning of powersystem expansion starts with the forecast of anticipated load requirement. Accurate loadforecast can be helpful in developing a power supply strategy and development plan,especially for developing countries where the demand is increased with dynamic andhigh growth rate. This thesis proposes a peak load forecast model using ArtificialNeural Networks (ANNs) with Multilayer Perceptron (MLP) and Backpropagation (BP)algorithm. The model can be used to forecast the monthly peak load frofn one month tothree years. The factors that reflect weather and economic variation are selected basedon correlation coefficients. A case study is performed by using the historical peak loaddata of Vientiane Capital of Lao PDR to demonstrate the accuracy of the proposedmethod. The peak load forecast model is shown to be simple and highly accurate. TheMean Absolute Percentage Error (MAPE) of the proposed model is around 2.8percentages.

King Mongkut's University Technology Thonburi. Library

Address: กรุงเทพมหานคร

Email: info.lib@mail.kmutt.ac.th

Name: Kosin Chamnongthai

Role: Advisor

Name: Anawach Sangswang

Role: Advisor

Created: 2004

Issued: 2007-07-20

Modified: 2010-12-19

วิทยานิพนธ์/Thesis

ISBN: 9741839391

CallNumber: ENE514

eng

Laos

Vientiane

DegreeName: Master of Engineering

Level: Master's Degree

Descipline: Electrical and Information Engineering

Grantor: King Mongkut's University of Technology Thonburi

©copyrights King Mongkut's University of Technology Thonburi

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