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Electricity Load Forecasting for the Australian Market Case Study

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Electricity Load Forecasting for the Australian Market Case Study

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19 Jun 2011 (Updated )

This is a case study of forecasting short-term electricity loads for the Australian market.

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Description

This is a case study of how MATLAB can be used to forecast short-term electricity loads for the Australian market using Sydney temperature and NSW histroical load data sets. Nonlinear regression and neural network modeling techniques are used to demonstrate accurate modeling using historical, seasonal, day-of-the week, and temperature data.

Highlights include:

• Forecasting short-term electricity loads and prices

• Accessing data from regional wholesale electricity markets

• “White-box” modeling using customisable algorithms and viewable-source functions

• Automatic Report Publishing

This case study is for practitioners at power generators, utilities or energy trading groups whose focus is transmission planning, distribution operations, derivative valuation, or quantitative analysis. Familiarity with MATLAB is not required.

Required Products MATLAB Builder EX
MATLAB Compiler
Neural Network Toolbox
Statistics Toolbox
MATLAB release MATLAB 7.12 (R2011a)
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Comments and Ratings (1)
16 Feb 2012 Faiz Mahdi

Hi David

I am usinf Artificial Neural network in my work to predict a model that can be used same experiments information to predict new results with less error ratio in comparison to experimental and theoretical ones.

I have done some work and got results but the error ratio is still high.

If you can help me or you know any one how is doing this work please send me back on my email, faizmaa@hotmail.co.uk

Regards

Faiz

Updates
30 Jun 2011

Added pdf of the presentation + file updates

30 Jun 2011

Change to description

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