Modified Gravitational Search Algorithm for Energy Demand Estimation of Turkey

Abstract

Estimation of energy demand beforehand is a quite significant problem in respect of economy and sources of country. In this study, Gravitational Search Algorithm (GSA) was modified by making some innovations in GSA and called as Modified Gravitational Search Algorithm (MGSA). Energy demand estimation is conducted through the relationship between the increase in economic indicators in Turkey and energy consumption. Estimation was actualized by using gross domestic product (GSYH), importation, exportation and demography for energy demand estimation and both linear and exponential equations. Energy demand between the years 2017-2037 was predicted by using the data belong to 1997-2011. The years between 2012 and 2016 were used as test data. It was observed that the results acquired via MGSA estimate better compared to GSA results.

Keywords

• Gravitational search algorithm,Energy demand,Estimation,Turkey

Modified Gravitational Search Algorithm for Energy Demand Estimation of Turkey

Abstract

Ülke ekonomisi ve kaynakları bakımından enerji talebini önceden tahmin etmek çok önemli bir problemdir. Bu çalışmada, Yerçekimi Arama Algoritması (YAA) ile YAA’da yapılan bazı yenilikler yapılarak modifiye edilmiş ve Modifiye Yerçekimi Arama Algoritması (MYAA) olarak adlandırılmıştır. Enerji talep tahmini, Türkiye’deki ekonomik göstergelerin artışı ile enerji tüketimi arasındaki ilişki ile gerçekleşmektedir. Enerji talep tahmini için gayri safi yurtiçi hasıla (GSYH), ithalat, ihracat ve nüfus bilgileri hem lineer hem de üssel denklemler kullanılarak tahmin işlemi gerçekleştirildi. 1997-2011 yılları arasındaki veriler kullanılarak 2017-2037 yılları arasındaki enerji talebi tahmin edilmiştir. 2012 ile 2016 yılları ise test verisi olarak kullanılmıştır. MGSA ile elde edilen sonuçlar GSA sonuçlarına göre daha iyi bir tahmin gerçekleştirdiği görülmüştür.

Keywords

• Yerçekimi arama algoritması,Enerji talebi,Tahmin,Türkiye

References

1. [1] M. Beskirli, H. Hakli, and H. Kodaz, "The energy demand estimation for Turkey using differential evolution algorithm," Sādhanā, vol. 42, pp. 1705-1715, 2017.
2. [2] I. Dincer and S. Dost, "Energy intensities for Canada," Applied Energy, vol. 53, pp. 283-298, 1996.
3. [3] E. Aktaş and O. Alioğlu, "Türkiye’de enerji sektörü analizi: Marmara bölgesi termik santraller örneği," Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, vol. 21, 2012.
4. [4] M. D. Toksarı, "Ant colony optimization approach to estimate energy demand of Turkey," Energy Policy, vol. 35, pp. 3984-3990, 2007.
5. [5] V. Ş. Ediger and S. Akar, "ARIMA forecasting of primary energy demand by fuel in Turkey," Energy Policy, vol. 35, pp. 1701-1708, 2007.
6. [6] V. Ş. Ediger and H. Tatlıdil, "Forecasting the primary energy demand in Turkey and analysis of cyclic patterns," Energy Conversion and Management, vol. 43, pp. 473-487, 2002.
7. [7] Z. Yumurtaci and E. Asmaz, "Electric energy demand of Turkey for the year 2050," Energy Sources, vol. 26, pp. 1157-1164, 2004.
8. [8] M. Akkurt, O. F. Demirel, and S. Zaim, "Forecasting Turkey’s natural gas consumption by using time series methods," European Journal of Economic and Political Studies, vol. 3, pp. 1-21, 2016.

9. [9] M. Mucuk and D. Uysal, "Turkey’s energy demand," Current Research Journal of Social Sciences, vol. 1, pp. 123-128, 2009.
10. [10] Z. Dilaver and L. C. Hunt, "Industrial electricity demand for Turkey: a structural time series analysis," Energy Economics, vol. 33, pp. 426-436, 2011.
11. [11] A. Sözen and E. Arcaklioğlu, "Prospects for future projections of the basic energy sources in Turkey," Energy Sources, Part B, vol. 2, pp. 183-201, 2007.
12. [12] M. Kankal, A. Akpınar, M. İ. Kömürcü, and T. Ş. Özşahin, "Modeling and Forecasting of Turkey’s Energy Consumption Using Socio-economic and Demographic Variables," Applied Energy, vol. 88, pp. 1927-1939, 2011.
13. [13] A. Sozen, E. Arcaklioglu, and M. Ozkaymak, "Modelling of Turkey's net energy consumption using artificial neural network," International Journal of Computer Applications in Technology, vol. 22, pp. 130-136, 2005.
14. [14] H. Ceylan and H. K. Ozturk, "Estimating energy demand of Turkey based on economic indicators using genetic algorithm approach," Energy Conversion and Management, vol. 45, pp. 2525-2537, 2004.
15. [15] S. Haldenbilen and H. Ceylan, "Genetic algorithm approach to estimate transport energy demand in Turkey," Energy Policy, vol. 33, pp. 89-98, 2005.
16. [16] M. S. Kıran, E. Özceylan, M. Gündüz, and T. Paksoy, "A novel hybrid approach based on particle swarm optimization and ant colony algorithm to forecast energy demand of Turkey," Energy conversion and management, vol. 53, pp. 75-83, 2012.
17. [17] A. Ünler, "Improvement of energy demand forecasts using swarm intelligence: The case of Turkey with projections to 2025," Energy Policy, vol. 36, pp. 1937-1944, 2008.
18. [18] M. S. Kıran and M. Gündüz, "A recombination-based hybridization of particle swarm optimization and artificial bee colony algorithm for continuous optimization problems," Applied Soft Computing, vol. 13, pp. 2188-2203, 2013.
19. [19] H. Uguz, H. Hakli, and O. K. Baykan, "A New Algorithm Based on Artificial Bee Colony Algorithm for Energy Demand Forecasting in Turkey," in 2015 4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT), 2015, pp. 56-61.
20. [20] M. F. Tefek, H. Uğuz, and M. Güçyetmez, "A new hybrid gravitational search–teaching–learning-based optimization method for energy demand estimation of Turkey," Neural Computing and Applications, pp. 1-16, 2017.
21. [21] M. F. Tefek and U. Harun, "Estimation of Turkey Electric Energy Demand until Year 2035 Using TLBO Algorithm," International Journal of Intelligent Systems and Applications in Engineering, vol. 4, pp. 48-52, 2016.
22. [22] E. Rashedi, H. Nezamabadi-Pour, and S. Saryazdi, "GSA: A Gravitational Search Algorithm," Information Sciences, vol. 179, pp. 2232-2248, Jun 13 2009.
23. [23] J. Xin, G. Chen, and Y. Hai, "A Particle Swarm Optimizer with Multi-stage Linearly-Decreasing Inertia Weight," in 2009 International Joint Conference on Computational Sciences and Optimization, 2009, pp. 505-508.
24. [24] MOD. (2018). Medium Term Programme 2018-2020. Available: http://www.mod.gov.tr/Pages/content.aspx?l=99479284-12e6-4d7d-bb4d-10d2a19feded&i=21
25. [25] TSI. (2018). Main Statistics -Population and Demography. Available: http://www.turkstat.gov.tr/UstMenu.do?metod=temelist
26. [26] TURKSTAT. (2013, 16.11.2016). Turkish Statistical Institute. Available: http://www.turkstat.gov.tr/UstMenu.do?metod=temelist