Medium-Term Electricity Demand Forecasting Based on MARS

Date

2017-09-29

Author

İlseven, Engin
Göl, Murat

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The paper proposes use of multivariate adaptive regression splines (MARS) method to perform monthly electricity demand forecasting for medium-term. The model is developed based on specific example of Turkey; however is applicable to any other system. Performance of the proposed method is compared to that of multiple linear regression (MLR), generalized additive model (GAM), and artificial neural networks (ANN) methods. The validation process shows that the proposed model outperforms the other ones by test error and shows stable error performance.

Subject Keywords

Multiple linear regression, Generalized additive models, Multivariate adaptive regression splines, Artificial neural networks, Electricity demand forecasting

URI

https://hdl.handle.net/11511/55240

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar