Vol. 8 No. 1 (2020): Business & Management Studies: An International Journal
Articles

RETURN ON INVESTMENT ANALYSIS OF UNLICENSED SOLAR ENERGY PROJECTS IN TURKEY

Murat ERTUĞRUL
Assoc. Prof. Dr., Anadolu University
Mustafa Hakan SALDI
Doct. Student, Anadolu University

Published 2020-03-25

Keywords

  • Renewable Energy Industry, Solar Energy, Unlicensed Solar Energy Projects in Turkey, Return On Investment Rates
  • Yenilenebilir Enerji Endüstrisi, Güneş Enerjisi, Türkiye’deki Lisanslı Olmayan Güneş Enerjisi Projeleri, Yatırımın Getiri Oranları

How to Cite

ERTUĞRUL, M., & SALDI, M. H. (2020). RETURN ON INVESTMENT ANALYSIS OF UNLICENSED SOLAR ENERGY PROJECTS IN TURKEY. Business & Management Studies: An International Journal, 8(1), 903–923. https://doi.org/10.15295/bmij.v8i1.1314

Abstract

First of all, this study aims to show how the power size and currency affect the return on investment percentages of unlicensed solar energy projects in Turkey. Commonly, the investors have confusions on their minds while taking investment decisions. Particularly, there are definite variables which may affect a solar energy project’s return on investment percentage and so the research question of how a multiple regression model can represent this percentage comes back to minds too. In order to simulate investment scenarios, this study is designed by using the sample of unlicensed solar energy installations which have the capacity of 250 KW, 500 KW and 1000 KW. According to the cash flow analyses for these samples the effects of power size and currency variables to return on investment percentages are observed. Therefore, the multiple regression model of return on investment percentages is offered by taking into account the power capacity and currency as independent variables to estimate the future cash flows by comparing each cases. As a result, the correlations are observed between dependent variable and independent variables. Especially, the power capacity has significant effect on return on investment rates of projects in accordance with the fundamental rule of risk-reward relation in finance. Also, the share of currency risk is calculated to prove how the volatility in currency index may affect the return on investment rates.

Downloads

Download data is not yet available.

References

  1. Bazilian, M., Onyeji, I., Liebreich, M., MacGill, I., Chase, J., Shah, J., Gielen, D., Arent, D., Landfear, D., Zhengrong, S. (2013). Re-considering the economics of photovoltaic power. Renewable Energy, 53, 329-338.
  2. Büyüközkan, G., Güleryüz, S. (2016). An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. International Journal of Production Economics, 182, 435-448.
  3. Büyüközkan, G., Güleryüz, S. (2017). Evaluation of Renewable Energy Resources in Turkey using an integrated MCDM approach with linguistic interval fuzzy preference relations. Energy, 123, 149-163.
  4. El-Sebaii, A.A., Al-Ghamdi, A.A., Al-Hazmi, F.S., Faidah, S. (2009). Estimation of global solar radiation on horizontal surfaces in Jeddah, Saudi Arabia. Energy Policy, 37(9), 3645-3649.
  5. Kıray, V., Şağbanşua, L. (2013). Barriers in front of solar energy plants in Turkey and investment analysis of solution scenarios-case study on a 10 MW system. Journal of Renewable and Sustainable Energy, 5(4), 041812.
  6. Muhammad-Sukki, F., Hawa Abu-Bakar, H., Munir, A.B., Hajar Mohd Yasin, S., Ramirez-Iniguez, R., McMeekin, S.G., Stewart, B.G., Sarmah, N., Mallick, T.K., Ruzairi (2014). Feed-in tariff for solar photovoltaic: The rise of Japan. Renewable Energy, 68, 636-643.
  7. Shrimali, G., Kniefel, J. (2011). Are government policies effective in promoting deployment of renewable electricity resources? Energy Policy, 39(9), 4726-4741.