Prediction of Renewable Energy Production Using Grey Systems Theory

Darvishi Salookolaei, D.; Babaei, P.; Heydari Gorji, S.

doi:10.22075/ijnaa.2019.4395

Prediction of Renewable Energy Production Using Grey Systems Theory

Document Type : Special issue editorial

Authors

D. Darvishi Salookolaei ¹

P. Babaei ¹

S. Heydari gorji ²

¹ Department of Mathematics, Payame Noor University, Tehran, Iran

² Department of Management, Payame Noor University, Tehran, Iran

10.22075/ijnaa.2019.4395

Abstract

Due to the reduction of renewable energy resources such as fossil fuels, the energy crisis is one of the most critical issues in today’s world. The application of these resources brings about many environmental pollutions that lead to global warming. Therefore, various countries have attempted to reduce potential damage and use renewable energies by the introduction and promotion of renewable energies as an essential strategy to reduce CO2 emissions and to find alternatives to fossil energy in the transportation and electricity generation sectors. This study attempts to predict the production process of renewable energies in Iran by 2025 and study the characteristics of this energy and its usage in the world and Iran. Since there are very few data in this field, four grey prediction models are used including GM(1,1), DGM(2,1), Grey Verhulst and FGM(1,1) models. According to the three indices of the error values of MSE, RMSE, and MAPE, all the predictions are done by the methods above are among the best prediction methods. By examining the results achieved, FGM(1,1)method was the best model concerning its less error than other models and has estimated 16740.45 MW for renewable energy production in 2025.

Keywords

Prediction

Grey system

Absolute prediction error

Renewable Energy

GM(1