Short term electricity load forecasting using Artificial Neural Network (ANN) / Muhammad Zakwan Mohd Zuki
This paper has presents a study of electricity load forecasting demand by using artificial neural network (ANN). Generally, there are three levels of processing forecasting data using artificial neural network (ANN) which are input layer, hidden layer and output layer. This method was developed usin...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2014
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| Online Access: | https://ir.uitm.edu.my/id/eprint/84574/1/84574.pdf https://ir.uitm.edu.my/id/eprint/84574/ |
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| Summary: | This paper has presents a study of electricity load forecasting demand by using artificial neural network (ANN). Generally, there are three levels of processing forecasting data using artificial neural network (ANN) which are input layer, hidden layer and output layer. This method was developed using MATLAB software which produced the accurate result of this load forecasting. Mean Absolute Percentage Error (MAPE) was applied to show the differences between predicted value and actual load data. The study forecasts the amount of consumed in the next 24-hours. Table of historical hourly loads of DUKE, USA from 26th March 2012 until 4th July 2012 was used in this paper. Forecasting load demand is very important for the operation of generating electricity supply companies because it helps to make decisions to generate enough power electric to consumer as well as to control operation of electric usage of the company's infrastructure. |
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