Original scientific paper

https://doi.org/10.17559/TV-20180814115917

Short Term Load Forecasting for Turkey Energy Distribution System with Artificial Neural Networks

Salih Tosun* ; Duzce University, Faculty of Technology, Dept. Electrical - Electronics Engineering, Konuralp Yerleşkesi, 81620 Duzce / Turkey
Ali Öztürk ; Duzce University, Faculty of Technology, Dept. Electrical - Electronics Engineering, Konuralp Yerleşkesi, 81620 Duzce / Turkey
Fatih Taşpinar ; Duzce University, Faculty of Technology, Dept. Electrical - Electronics Engineering, Konuralp Yerleşkesi, 81620 Duzce / Turkey

Abstract

The constant increase in consumption of electricity has become one of the biggest problems today. The evaluation of energy resources has also made it worthwhile to consume it. In this respect, the transmission of electric energy and the operation of power systems have become important issues. As a result, reliable, high quality and affordable energy supply has become the most important task of operators. Realizing these elements can certainly be accomplished with good planning. One of the most important elements of this planning is undoubtedly consumption estimates. Therefore, knowing when consumers will consume energy is of great importance for operators as well as energy producers. Consumption estimates or, in other words, load estimates are also important in terms of the price balance that will occur in the market. In this study, the short-term load estimation of Düzce, Turkey is performed with Artificial Neural Networks (ANN). In the study, the April values were taken as reference and the estimates were obtained according to the input results of this month. As a result of this study, it is seen that the load consumption with nonlinear data can be successfully forecasted by ANN.

Keywords

Artificial Neural Networks (ANN); Electric Energy; Short-Term Load Forecasting

Hrčak ID:

228498

URI

https://hrcak.srce.hr/228498

Publication date:

27.11.2019.

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