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Forecasting of electricity consumption based on soft computing for advancing performance: The case study for the Organization of Petroleum Exporting Countries (OPEC)

Chiroma, Haruna, Abdullah, Khan, Hamza, Mukhtar F., Shuib, Liyana, Idrees, Muhammad, Herawan, Tutut
Energy 2016
Markov chain, algorithms, case studies, economic development, electric energy consumption, electricity, energy conservation, issues and policy, models
Forecasting of electricity consumption can help policy makers to properly plan for economic development and energy conservation by avoiding excessive consumption of electricity through enhanced operational strategy. There is a long run relationship between electricity consumption and the economic development in all the Organization of Petroleum Exporting Countries (OPEC) member countries. To improve electricity consumption forecasting performance, this paper proposed an alternative intelligent soft computing method for the forecasting of OPEC electricity consumption. The modelling of OPEC electricity consumption forecasting based on Cuckoo Search Algorithm via Lévy flights is proposed. The proposed method is found to be effective, efficient, consistent, and robust compared to the electricity consumption forecasting methods that have already been discussed by researchers in the literature. Our proposal can be an alternative method of forecasting OPEC electricity consumption with an improved performance. In turn, energy conservation can be motivated in the 12 OPEC member countries.