Title: Prediction of Iran's renewable energy generation in the fifth development plan
Authors: S. Kamal Chaharsooghi; Mohsen Rezaei
Addresses: Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran ' Department of Industrial Engineering, Tarbiat Modares University, Tehran, Iran
Abstract: Although Iran has rich reserves of oil and gas, it should not only rely on these resources and should take policies to develop renewable energies (REs). This study developed two forecasting models (ANN and ARIMA) to estimate the renewable energy generation of Iran. After comparison of the developed models, the best model is chosen to predict the renewable energy generation by 2015. Then the prediction is compared with government plan by the end of the Fifth Five-Year Economic Development Plan. The results indicated that RE generation will increase, but, the government will not meet its objectives of producing 5% of total electric power generation through RE resources.
Keywords: power generation forecasting; renewable energy; artificial neural networks; ANNs; autoregressive integrated moving average; ARIMA; Iran; energy planning; government policy.
DOI: 10.1504/IJSOM.2016.078073
International Journal of Services and Operations Management, 2016 Vol.25 No.1, pp.120 - 133
Received: 19 Dec 2014
Accepted: 12 Feb 2015
Published online: 01 Aug 2016 *