Improved Grey Verhulst model with the constant term and its application to forecast energy demand
Makaleler > Tam Makale · 2022
Yazarlar: Sevcan DEMİR ATALAY, Gülben ÇALIŞ, MELTEM ADIYAMAN
PROCEEDINGS OF THE INSTITUTION OF CIVIL ENGINEERS: ENGINEERING SUSTAINABILITY, SCI Expanded İndekslerine Giren Dergi, Uluslararası, Wos, 2022, cilt 175, ss 154-164
Özet
<p>The importance of accurate energy demand modelling has increased to support the decision making of policymakers for</p><p>ensuring a safe energy supply. However, forecasting energy demand has several difficulties due to the complexity of the</p><p>supply line, demand increase, non-linearity of data and volatility of energy usage. In this study, an improved grey Verhulst</p><p>model with a constant term (GVMCT), which is based on the grey model, is introduced for improving the accuracy of</p><p>energy demand prediction models. Within this context, the total residential electricity demand of both the USA and Turkey</p><p>is modelled by way of linear and quadratic trend models, as well as three grey models, including the proposed GVMCT</p><p>model. The effectiveness of the models is assessed based on the mean absolute error (MAE), mean squared error and root</p><p>mean square error. The results show that the linear trend is the best-performing model, with an MAE of 34 564.81844, for</p><p>the US data, whereas the proposed GVMCT, with an MAE of 4130.086917, outperforms all models for the data of Turkey.</p>