Modeling and prediction of Turkey's electricity consumption using Support Vector Regression

Kadir Kavaklioglu

Applied Energy, 2011, vol. 88, issue 1, 368-375

Abstract: Support Vector Regression (SVR) methodology is used to model and predict Turkey's electricity consumption. Among various SVR formalisms, [epsilon]-SVR method was used since the training pattern set was relatively small. Electricity consumption is modeled as a function of socio-economic indicators such as population, Gross National Product, imports and exports. In order to facilitate future predictions of electricity consumption, a separate SVR model was created for each of the input variables using their current and past values; and these models were combined to yield consumption prediction values. A grid search for the model parameters was performed to find the best [epsilon]-SVR model for each variable based on Root Mean Square Error. Electricity consumption of Turkey is predicted until 2026 using data from 1975 to 2006. The results show that electricity consumption can be modeled using Support Vector Regression and the models can be used to predict future electricity consumption.

Keywords: Electricity; consumption; Support; Vector; Regression; Turkey; Energy; modeling; Time; series; Prediction (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (52)

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