The electricity demand has become increasingly significant for the financial decision makers with rapid economic growth. In order to achieve a sustainable economic growth, continuous and adequate power supply is crucial. Due to the electricity is unable to be stored economically and has a characteristic of coincidence of generation and consumption, forecasting electricity demand accurately is of great importance in order to balance supply and demand. Turkey, an emerging market with one of the most rapid economic growth rate in the world, should consider forecasting the gross electricity demand. As it is known, there exists a high correlation between growth rate of gross domestic product (GDP) and electricity demand in developing countries. Therefore, unlike many other forecasting models for electricity demand, a single parameter (GDP in line with the purchasing power parity) has been used to estimate gross annual electricity demand of Turkey in this empirical study. Three different forecasting methods, namely; time series, regression and fuzzy logic techniques have been applied to Turkish electricity demand data and then compared according to the absolute relative errors (AREP) . Based on the AREP figures, it can be concluded that time series model has shown a slightly better forecasting performance than the other two methods for estimating gross annual electricity demand of Turkey based on the available data.


  • Due to urbanization and fast economic growth, demand for energy and the necessity of new investments in energy sector have been rising

  • Many studies dealing with electricity demand forecast reveals that economic growth and electricity demand has a high correlation

  • Between the years 2000-2011 electricity demand in Turkey grew by 5,68% on average and over the same period the average gross domestic product increased by 4,36% on average (Figure 1)

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Due to urbanization and fast economic growth, demand for energy and the necessity of new investments in energy sector have been rising. Turkey has lower per capita consumption (one fourth of IEA average) it is expected to increase as the economy and energy demand grows (Energy Market Regulatory Authority, 2012). It is believed that the demand for electricity’s continuously increase in the forthcoming years in Turkey This increase in demand is expected to be proportional to the country’s economic growth rather than network expansion due to population rise and new settlement areas. Several analysts have tried to estimate electricity/energy demand of Turkey by models like; Autoregressive Integrated Moving Average (ARIMA) modelling and partial adjustment model (Akay & Atak, 2007), Grey Prediction with Rolling Mechanism (GPRM) (Hamzacebi, 2007), artificial neural networks (ANN) (Ceylan & Ozturk, 2005), fuzzy logic approach (Kucukali & Baris, 2010) and structural time series method (Dilaver & Hunt, 2011). In order to construct a simple and practical model, unlike many other models, single parameter model is preferred in this empirical study

A Short Review of Turkish Electricity Market
Fuzzy Logic Model
Time Series Model
Data and Methodology
Fuzzy Sets and Rules Used in the Analyses
Conclusion and Remarks

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