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Middle Anatolian Region Short-Term Load Forecasting Using Artificial Neural Networks

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Abstract:

In recent years, several studies of short-term load forecasting using different of artificial neural network structures have been reported. In this paper, an application of short-term load forecasting is investigated by multilayer perceptron structure. Actual load and temperature data of the Middle Anatolian Region in the years 2002 and 2003 are used for this investigation. In this study, maximum temperature, minimum temperature, and day type factors are used to construct the forecasting model. Also, load forecasting for the same region is obtained by the regression method to compare the effectiveness of the artificial neural network method.

Keywords: artificial neural networks; short-term load forecasting; similarity based load forecasting

Document Type: Research Article

DOI: http://dx.doi.org/10.1080/15325000500419284

Affiliations: Istanbul Technical University, Maslak, Istanbul, Turkey

Publication date: June 1, 2006

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