GMDH-type neural network-based monthly electricity demand forecasting of Turkey

Ali Volkan AKKAYA

doi:https://doi.org/10.35860/iarej.766762

Makale detayları

GMDH-type neural network-based monthly electricity demand forecasting of Turkey

Yazarlar:

Ali Volkan AKKAYA

Yayıncı:

Ceyhun YILMAZ

Ana Başlıklar:

Mühendislik ve uygulamalı operasyonlar

Dergi:

International Advanced Researches and Engineering Journal 2021 Vol.5 Issue 1, pp.53-60

Belge Tipi:

Makale

Yayın Tarihi:

4/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000469312

Sıklık:

Üç Yıllık

eISSN:

2618-575X

DOI:

https://doi.org/10.35860/iarej.766762

Özet:

 

In this study, it was aimed to develop an accurate forecasting model for the monthly electricity demand of Turkey in the medium-term. For this purpose, the Group Method of Data Handling (GMDH)-type Neural Network (NN) approach was used to structure a nonlinear time-series based forecasting model.  A large dataset containing monthly electricity demand was considered for the period of 2003-2018. The developed model was tested in the period of 2019/01-2019/11 in order to determine the generalization ability of the model. The test results showed that the developed model was very close to actual values. The obtained test performances were 2.10 % for mean absolute percentage error (MAPE), 2.36 % for root mean square percentage error (RMSPE) and 0.869 for coefficient of determination (R2). In addition, results of the proposed GMDH-type NN model were compared with the forecasting results of a literature study. The comparison revealed that GMDH-type NN was a better approach for forecasting the monthly electricity demand of Turkey. Finally, the developed model was utilized to forecast monthly electricity demand in the period of 2019/12-2020/12.

Makale detayları

GMDH-type neural network-based monthly electricity demand forecasting of Turkey

Yazarlar: Ali Volkan AKKAYA

Yayıncı: Ceyhun YILMAZ

Ana Başlıklar: Mühendislik ve uygulamalı operasyonlar

Dergi: International Advanced Researches and Engineering Journal 2021 Vol.5 Issue 1, pp.53-60

Belge Tipi: Makale

Yayın Tarihi: 4/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000469312

Sıklık: Üç Yıllık

eISSN: 2618-575X

DOI: https://doi.org/10.35860/iarej.766762

Sayı

Yazarlar:

Ali Volkan AKKAYA

Yayıncı:

Ceyhun YILMAZ

Ana Başlıklar:

Mühendislik ve uygulamalı operasyonlar

Dergi:

International Advanced Researches and Engineering Journal 2021 Vol.5 Issue 1, pp.53-60

Belge Tipi:

Makale

Yayın Tarihi:

4/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000469312

Sıklık:

Üç Yıllık

eISSN:

2618-575X

DOI:

https://doi.org/10.35860/iarej.766762