A comparative Study of Forecasting the Electrical Demand in Basra city using Box-Jenkins and Modern Intelligent Techniques
The electrical consumption in Basra is extremely nonlinear; so forecasting the monthly required of electrical consumption in this city is very useful and critical issue. In this Article an intelligent techniques have been proposed to predict the demand of electrical consumption of Basra city. Inte...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
College of Engineering, University of Basrah
2015-06-01
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| Series: | Iraqi Journal for Electrical and Electronic Engineering |
| Subjects: | |
| Online Access: | http://ijeee.org/volums/volume11/IJEEE11PDF/paper1112.pdf |
| Summary: | The electrical consumption in Basra is extremely nonlinear; so forecasting the monthly required of
electrical consumption in this city is very useful and critical issue. In this Article an intelligent techniques have been
proposed to predict the demand of electrical consumption of Basra city. Intelligent techniques including ANN and
Neuro-fuzzy structured trained. The result obtained had been compared with conventional Box-Jenkins models
(ARIMA models) as a statistical method used in time series analysis. ARIMA (Autoregressive integrated moving
average) is one of the statistical models that utilized in time series prediction during the last several decades. Neuro-
Fuzzy Modeling was used to build the prediction system, which give effective in improving the predict operation
efficiency. To train the prediction system, a historical data were used. The data representing the monthly electric
consumption in Basra city during the period from (Jan 2005 to Dec 2011). The data utilized to compare the proposed
model and the forecasting of demand for the subsequent two years (Jan 2012-Dec 2013). The results give the
efficiency of proposed methodology and show the good performance of the proposed Neuro-fuzzy method compared
with the traditional ARIMA method. |
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| ISSN: | 1814-5892 2078-6069 |