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ENERGY-POPULATION EVALUATION AND PROJECTION OF KÜTAHYA PROVINCE

Year 2023, Issue: 054, 224 - 238, 30.09.2023
https://doi.org/10.59313/jsr-a.1209077

Abstract

Examination of the energy situation is essential, especially for countries that are dependent on foreign Energy terms of Energy. Energy consumption, which increases indirectly with population and technology, needs to be evaluated in the short, medium, and long term. Energy projections are one of the most critical issues in the development planning of states. In this study, the population and energy status of the Kütahya province of Turkey were examined in detail, and the population and Energy projections were evaluated. While reviewing the population projection, predictions have been prepared depending on the population changes of the last five years, the last ten years, the last 15 years, and the previous 20 years, together with the projection prepared by the Turkish Statistical Institute. While preparing the electrical energy consumption projection of Kütahya province, evaluations were made according to three different scenarios prepared by the Ministry of Energy and Natural Resources of the Republic of Turkey. Accordingly, the electricity consumption of Kütahya province in 2039; has been determined as 2.71 billion kWh according to the 1st scenario, 2.96 billion kWh according to the 2nd scenario, and 3.27 billion kWh according to the 3rd scenario.

References

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  • [2] Republic of Turkey Ministry of Energy and Natural Resources. (2022). Republic of Turkey Ministry of Energy and Natural Resources – electricity.
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  • [4] Kan, X., Reichenberg, L. and Hedenus, F. (2021). The impacts of the electricity demand pattern on electricity system cost and the electricity supply mix: A comprehensive modeling analysis for Europe. Energy, 235 (1), 121239.
  • [5] Wu, W. Z., Pang, H., Zheng, C., Xie, W. and Liu, C. (2021). Predictive analysis of quarterly electricity consumption via a novel seasonal fractional nonhomogeneous discrete grey model: a case of Hubei in China. Energy, vol. 229 (1), 120714.
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  • [8] Zhang, M., Cheng, C. H. and Ma, H. Y. (2020). Projection of residential and commercial electricity consumption under SSPs in Jiangsu province, China. Advances in Climate Change Research, 11 (2), 131–140.
  • [9] Soummane, S. and Ghersi, F. (2022). Projecting Saudi sectoral electricity demand in 2030 using a computable general equilibrium model. Energy Strategy Reviews, 39 (1), 100787.
  • [10] da Silva, F. L. C., Cyrino Oliveira, F. L. and Souza, R. C. (2019). A bottom-up bayesian extension for long term electricity consumption forecasting. Energy, 167 (1), 198–210.
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  • [12] Roberts, M. J., Zhang, S., Yuan, E., Jones, J., and Fripp, M. (2022). Using temperature sensitivity to estimate shiftable electricity demand. iScience 25 (9), 104940.
  • [13] Republic of Türkiye Kutahya Governorship. (2021). Information about Kütahya.
  • [14] Ozgur, M. A. and Köse, G. (2013). A technoeconomic analysis of solar photovoltaic power systems: Kütahya case study. Energy Sources, Part A: Recovery, Utilization and Environmental Effects, 35 (1), 42–57.
  • [15] Ministry of Energy and Natural Resources of the Republic of Turkey. (2020). Solar Energy Potential Atlas.
  • [16] European Commission. (2017). JRC photovoltaic geographical information system (PVGIS).
  • [17] Climate-data.org. (2021). İklim: Türkiye.
  • [18] Turkish Statistical Institute. (2021). Population results based on address.
  • [19] Republic of Türkiye Energy Market Regulatory Authority EPDK. (2021). Electricity market monthly sector reports.
  • [20] Turkish Statistical Institute. (2021). Türkiye population and demography.
  • [21] Suddhendu, B. (1988). Stochastic Processes in Demography and Applications, John Wiley & Sons.
  • [22] Republic of Türkiye Energy Market Regulatory Authority EPDK. (2021). General Directorate of Energy Affairs reports.
Year 2023, Issue: 054, 224 - 238, 30.09.2023
https://doi.org/10.59313/jsr-a.1209077

Abstract

References

  • [1] International Atomic Energy Agency. (2019). Energy, electricity and nuclear power estimates for the period up to 2050, reference data series no. 1.
  • [2] Republic of Turkey Ministry of Energy and Natural Resources. (2022). Republic of Turkey Ministry of Energy and Natural Resources – electricity.
  • [3] Şişman, N., Sofuoğlu, M. A., Aras, N. and Aras, H. (2022). Modelling of Turkey’s energy consumption using artificial neural networks. Advanced Engineering Forum, 44 (1), 73-86.
  • [4] Kan, X., Reichenberg, L. and Hedenus, F. (2021). The impacts of the electricity demand pattern on electricity system cost and the electricity supply mix: A comprehensive modeling analysis for Europe. Energy, 235 (1), 121239.
  • [5] Wu, W. Z., Pang, H., Zheng, C., Xie, W. and Liu, C. (2021). Predictive analysis of quarterly electricity consumption via a novel seasonal fractional nonhomogeneous discrete grey model: a case of Hubei in China. Energy, vol. 229 (1), 120714.
  • [6] Belançon, M. P. (2021). Brazil electricity needs in 2030: trends and challenges. Renewable Energy Focus, 36 (1), 89–95.
  • [7] Cekinir, S., Ozgener, O. and Ozgener, L. (2022). Türkiye’s energy projection for 2050. Renewable Energy Focus, 43 (1), 93–116.
  • [8] Zhang, M., Cheng, C. H. and Ma, H. Y. (2020). Projection of residential and commercial electricity consumption under SSPs in Jiangsu province, China. Advances in Climate Change Research, 11 (2), 131–140.
  • [9] Soummane, S. and Ghersi, F. (2022). Projecting Saudi sectoral electricity demand in 2030 using a computable general equilibrium model. Energy Strategy Reviews, 39 (1), 100787.
  • [10] da Silva, F. L. C., Cyrino Oliveira, F. L. and Souza, R. C. (2019). A bottom-up bayesian extension for long term electricity consumption forecasting. Energy, 167 (1), 198–210.
  • [11] Pérez-García J, Moral-Carcedo J (2016) Analysis and long term forecasting of electricity demand trough a decomposition model: A case study for Spain. Energy 97:127–143.
  • [12] Roberts, M. J., Zhang, S., Yuan, E., Jones, J., and Fripp, M. (2022). Using temperature sensitivity to estimate shiftable electricity demand. iScience 25 (9), 104940.
  • [13] Republic of Türkiye Kutahya Governorship. (2021). Information about Kütahya.
  • [14] Ozgur, M. A. and Köse, G. (2013). A technoeconomic analysis of solar photovoltaic power systems: Kütahya case study. Energy Sources, Part A: Recovery, Utilization and Environmental Effects, 35 (1), 42–57.
  • [15] Ministry of Energy and Natural Resources of the Republic of Turkey. (2020). Solar Energy Potential Atlas.
  • [16] European Commission. (2017). JRC photovoltaic geographical information system (PVGIS).
  • [17] Climate-data.org. (2021). İklim: Türkiye.
  • [18] Turkish Statistical Institute. (2021). Population results based on address.
  • [19] Republic of Türkiye Energy Market Regulatory Authority EPDK. (2021). Electricity market monthly sector reports.
  • [20] Turkish Statistical Institute. (2021). Türkiye population and demography.
  • [21] Suddhendu, B. (1988). Stochastic Processes in Demography and Applications, John Wiley & Sons.
  • [22] Republic of Türkiye Energy Market Regulatory Authority EPDK. (2021). General Directorate of Energy Affairs reports.
There are 22 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Articles
Authors

Oguz Ozan Yolcan 0000-0002-6664-5675

Ramazan Köse 0000-0001-6041-6591

Publication Date September 30, 2023
Submission Date November 23, 2022
Published in Issue Year 2023 Issue: 054

Cite

IEEE O. O. Yolcan and R. Köse, “ENERGY-POPULATION EVALUATION AND PROJECTION OF KÜTAHYA PROVINCE”, JSR-A, no. 054, pp. 224–238, September 2023, doi: 10.59313/jsr-a.1209077.