Artificial neural networks in short term load forecasting / Zulkifle Ahmad
The artificial neuron network (ANN) technique for short-term load forecasting (STLF) has been proposed by several authors in order to evaluate ANN as a viable technique for STLF. Once we have to evaluate the performance of ANN methodology for practical considerations of STLF problem. This paper will...
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| 主要作者: | |
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| 格式: | Thesis |
| 語言: | English |
| 出版: |
2003
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| 主題: | |
| 在線閱讀: | https://ir.uitm.edu.my/id/eprint/67083/2/67083.pdf |
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| 總結: | The artificial neuron network (ANN) technique for short-term load forecasting (STLF) has been proposed by several authors in order to evaluate ANN as a viable technique for STLF. Once we have to evaluate the performance of ANN methodology for practical considerations of STLF problem. This paper wills presents the results of a study to look the effectiveness of next 1 hour ANN model in 24-hour load profile at the one time was compared with the previous load on 3 months load. Data from utilities were used in modeling and forecasting. In this thesis, the back propagation will be applied as the most popular technique in Artificial Neural Network. This model is propagated forward and the error between the actual and desired output is back propagated to obtain a minimize error closer to zero. From this study we can also find that whether the Short Term Load Forecasting, Artificial Neural Network is sensitive load forecast or not. |
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