Forecasting Turkey's Short Term Hourly Load with Artificial Neural Networks

Date

2010-04-22

Author

BİLGİÇ KÜÇÜKGÜVEN, MERİÇ
Girep, C. P.
ASLANOĞLU, SAİME YEŞER
AYDINALP KÖKSAL, MERİH

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Load forecasting is important necessity to provide economic, reliable, high grade energy. In this study, short term hourly load forecasting systems were developed for nine load distribution regions of Turkey using artificial neural networks (ANN) approach. ANN is the most commonly preferred approach for load forecasting. The mean average percent error (MAPE) of total hourly load forecast for Turkey is found as 1.81%.

Subject Keywords

Short term load forecasting, Artificial neural networks (ANN)

URI

https://hdl.handle.net/11511/67383

Collections

Department of Mechanical Engineering, Conference / Seminar

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Citation Formats

M. BİLGİÇ KÜÇÜKGÜVEN, C. P. Girep, S. Y. ASLANOĞLU, and M. AYDINALP KÖKSAL, “Forecasting Turkey’s Short Term Hourly Load with Artificial Neural Networks,” 2010, p. 0, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/67383.