Grey prediction with rolling mechanism for electricity demand forecasting of Turkey

Primary energy sources planning based on demand forecasting: The case of Turkey

“…The GM (1,1) has been used as a prediction tool in several different areas (Sum, 1991;Zhu and Cao, 1998;Wang, 2002;Mao and Chirwa, 2006;Chiang and Chen et al, 2008); Tang and Yin, 2012). Energy demand forecasting is another important usage area of grey prediction models (Yao et al, 2003;Zhou et al, 2006;Akay and Atak, 2007;Hsu and Chen, 2012;Chena and Wang, 2012;Lü and Lu, 2012;Chang et al, 2013).…”

Turkish aggregate electricity demand: An outlook to 2020

“…Comparing to the previous projections in Table 3 12 it can be seen that these forecasts are lower than, Ozturk and Ceylan [8], Hamzacebi [10] and Akay and Atak [11], but higher than Erdogdu [7] and Kavaklioglu et al [9]. 13 …”

“…4 Similar to Bakirtas et al [6], Erdogdu [7] undertakes a separate analysis to produce a forecast of future Turkish electricity demand. 5 The above summary highlights that Bakirtas et al [6], Erdogdu [7], Hamzacebi [10] and Akay and Atak [11] all made use of techniques that effectively only used past electricity consumption to drive their forecasts of electricity demand. They therefore ignored any demand relationship and the important interaction between electricity consumption and economic variables such as income and price.…”

“…Source: [4] and [1] There are only a limited number of previous academic studies focussing on Turkish aggregate electricity demand, although there has been an increase since the early 2000s. These include Bakirtas et al [6], Erdogdu [7], Ozturk and Ceylan [8], Kavaklioglu et al [9], Hamzacebi [10] and Akay and Atak [11]; some of which attempt to identify a Turkish aggregate electricity demand relationship, some of which attempt to forecast future aggregate electricity demand, and some of which attempt to both; these are briefly reviewed below. Bakirtas et al [6] used the cointegration technique with annual data to explore the relationship between per capita aggregate electricity consumption, income per capita, and price for the period 1962 to 1996.…”

The ELM Model to Estimate Energy Demand of China

“…In the course of research, some common prediction methods have been obtained, such as sectoral projection [1,2] , input-output model [3] , elastic coefficient method [4] , bottom-up model [5,6] , econometric model [7] , decomposition model [8,9] , system dynamics [10] , gray prediction [11,12] and other traditional methods [13] . The above-mentioned traditional prediction methods have made a certain contribution to the long strategic planning of energy.…”