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Journals / Bitlis Eren Üniversitesi Fen Bilimleri Dergisi / 2019 / Cilt: 8 - Sayı: 4

Modified Gravitational Search Algorithm for Energy Demand Estimation of Turkey

Mehmet BEŞKİRLİ
Mehmet Fatih TEFEK
Harun UĞUZ
Pages
1338–1348
Publication Date
2019-12-24
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It was observed that the results acquired via MGSA estimate better compared to GSA results.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Estimation of energy demand beforehand is a quite significant problem in respect of economy and sources of country.
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Key Findings & Data:Energy demand estimation is conducted through the relationship between the increase in economic indicators in Turkey and energy consumption.
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Conclusion & Impact:It was observed that the results acquired via MGSA estimate better compared to GSA results.
🔬Design:Research Article
📍Scope:2017-2037 Verileri
⚙️Variables:Yerçekimi arama algoritması · Enerji talebi · Tahmin

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.

Özet

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.

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Cite This Article

BEŞKİRLİ, M., TEFEK, M. F., UĞUZ, H. (2019). Modified Gravitational Search Algorithm for Energy Demand Estimation of Turkey. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, Cilt: 8 - Sayı: 4, 1338–1348. https://ajindex.com/articles/477703

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References (16)

  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. I. Dincer and S. Dost, "Energy intensities for Canada," Applied Energy, vol. 53, pp. 283-298, 1996
  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. M. D. Toksarı, "Ant colony optimization approach to estimate energy demand of Turkey," Energy Policy, vol. 35, pp. 3984-3990, 2007
  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. 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. Z. Yumurtaci and E. Asmaz, "Electric energy demand of Turkey for the year 2050," Energy Sources, vol. 26, pp. 1157-1164, 2004
  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. M. Mucuk and D. Uysal, "Turkey’s energy demand," Current Research Journal of Social Sciences, vol. 1, pp. 123-128, 2009
  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. 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. 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. 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. 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. S. Haldenbilen and H. Ceylan, "Genetic algorithm approach to estimate transport energy demand in Turkey," Energy Policy, vol. 33, pp. 89-98, 2005
  16. M. S. Kıran, E. Özceylan, M. Gündüz, and T. Pa