Öz
In this study, using Crystall Ball software Monte Carlo
Simulation (MCS) Model was used for evaluation of wind power plant (WPP)
investment. WPP project’s Net Present Value (NPV) were determined, by
simulating different combinations of input variables affecting the WPP
investments. Three different scenarios were used in the evaluation of the
project’s NPV. In the simulation results for three scenarios, the results of
the MCS analysis of the WPP investment’s NPV was obtained. End of the results,
MCS is a useful method for the evaluation of the WPP investmet.
Anahtar Kelimeler
Wind Power Investment Monte Carlo Simulation Senario Analysis
Kaynakça
- Ay, A. (2010). Energy Sources And Investment Project Assessment: A Case Study About Wind Energy In Turkey, Bahçeşehir üniversitesi, Yayımlanmış Yüksek Lisans Tezi, İstanbul.
- Desrochers, G., Blanchard, M., ve Sud, S., 1986, A Monte-Carlo simulation method for the economic assessment of the contribution of wind energy to power systems. IEEE Transactions on Energy Conversion, (4), 50-56.
- Frølunde, S. G., & Obling, P. E. (2010). Valuation models for wind farms under development.
- GWEC, 2016, Global Wind Statistics Annual Market Update 2015, http://www.gwec.net/wp-content/uploads/vip/GWEC-Global-Wind-2015-Report_ April-2016_22_04.pdf (Erişim: 14.10.2016)
- Hamamcıoğlu, (2010). Rüzgar Enerji Kaynaklı Elektrik Üretiminin Teknik/Ekonomik Analizi ve Yöresel Uygulaması, Yıldız Teknik Üniversitesi, Yayımlanmış Yüksek Lisans Tezi, İstanbul.
- Hançerlioğulları, A., (2006). Monte Carlo Simülasyon Metodu ve MCNP Kod Sistemi, Kastamonu. Education Journal, 14(2), 545-546.
- Hertzmark, D. I. (2007). Risk assessment methods for power utility planning. Energy Sector Management Assistance Program.The World Bank, Energy Sector Management Assistance Program (ESMAP), Washington D.C.
- Khindanova, I. (2013). A Monte Carlo Model of a Wind Power Generation Investment. The Journal of Applied Business and Economics, 15(1), 94.
- Liberman, E. J. (2003). A life cycle assessment and economic analysis of wind turbines using Monte Carlo simulation (No. Afıt/Gee/Env/03-16). Air Force Inst Of Tech Wright-Patterson Afb Oh School Of Engineerıng And Management.
- Madlener, R., & Wenk, C. (2008). Efficient investment portfolios for the Swiss electricity supply sector.
- Roques, F. A., Nuttall, W. J., & Newbery, D. M. (2006). Using probabilistic analysis to value power generation investments under uncertainty. University of Cambridge, Electricity Policy Research Group.
- Ross, S. A., Westerfield, R. W. ve Jaffe, J., 2010, Corporate Finance, Ninth Edition, ISBN 978-007-131308-7, NewYork. McGraw-Hill/Irwin.
- Simkins, B., & Simkins, R. (2013). Energy finance and economics: Analysis and valuation, risk management, and the future of energy (Vol. 606). John Wiley & Sons.
- Spinney, P. J., & Watkins, G. C. (1996). Monte Carlo simulation techniques and electric utility resource decisions. Energy Policy, 24(2), 155-163.
- TUREB, 2016, Türkiye Rüzgar Enerjisi İstatistik Raporu, http:// www.tureb.com.tr/files/yayinlar/temmuz_2016_istatistik.pdf (Erişim: 17.10.2016)
- Williams, S. K., Acker, T., Goldberg, M., ve Greve, M. (2008). Estimating the economic benefits of wind energy projects using Monte Carlo simulation with economic input/output analysis. Wind Energy, 11(4), 397-414.
- Cardell, J. B., & Anderson, C. L. (2010, January). Analysis of the system costs of wind variability through Monte Carlo simulation. In System Sciences (HICSS), 2010 43rd Hawaii International Conference on (pp. 1-8). IEEE.
Öz
Bu
çalışmada, Crystall Ball programı kullanılarak rüzgar enerjisi santral (RES)
yatırımlarının değerlendirilmesinde monte carlo simülasyon (MCS) modeli kullanılmıştır.
RES yatırımını etkileyen girdi değişkenlerin farklı kombinasyonları simüle
edilerek, projenin net bugünkü değeri (NBD) belirlenmeye çalışılmıştır.
Projenin NBD’sine ait değerlendirmede üç farklı senaryodan yararlanılmıştır. Üç
farklı senaryo için yapılan simülasyon sonuçlarında RES yatırımının NBD’sine
ait MCS analizi sonuçları elde edilmiştir. MCS modelinin RES yatırımlarının
değerlendirilmesinde kullanışlı bir model olduğu sonucuna ulaşılmıştır.
Anahtar Kelimeler
Rüzgar Enerjisi Yatırımları Monte Carlo Simülasyonu Senaryo analizi
Kaynakça
- Ay, A. (2010). Energy Sources And Investment Project Assessment: A Case Study About Wind Energy In Turkey, Bahçeşehir üniversitesi, Yayımlanmış Yüksek Lisans Tezi, İstanbul.
- Desrochers, G., Blanchard, M., ve Sud, S., 1986, A Monte-Carlo simulation method for the economic assessment of the contribution of wind energy to power systems. IEEE Transactions on Energy Conversion, (4), 50-56.
- Frølunde, S. G., & Obling, P. E. (2010). Valuation models for wind farms under development.
- GWEC, 2016, Global Wind Statistics Annual Market Update 2015, http://www.gwec.net/wp-content/uploads/vip/GWEC-Global-Wind-2015-Report_ April-2016_22_04.pdf (Erişim: 14.10.2016)
- Hamamcıoğlu, (2010). Rüzgar Enerji Kaynaklı Elektrik Üretiminin Teknik/Ekonomik Analizi ve Yöresel Uygulaması, Yıldız Teknik Üniversitesi, Yayımlanmış Yüksek Lisans Tezi, İstanbul.
- Hançerlioğulları, A., (2006). Monte Carlo Simülasyon Metodu ve MCNP Kod Sistemi, Kastamonu. Education Journal, 14(2), 545-546.
- Hertzmark, D. I. (2007). Risk assessment methods for power utility planning. Energy Sector Management Assistance Program.The World Bank, Energy Sector Management Assistance Program (ESMAP), Washington D.C.
- Khindanova, I. (2013). A Monte Carlo Model of a Wind Power Generation Investment. The Journal of Applied Business and Economics, 15(1), 94.
- Liberman, E. J. (2003). A life cycle assessment and economic analysis of wind turbines using Monte Carlo simulation (No. Afıt/Gee/Env/03-16). Air Force Inst Of Tech Wright-Patterson Afb Oh School Of Engineerıng And Management.
- Madlener, R., & Wenk, C. (2008). Efficient investment portfolios for the Swiss electricity supply sector.
- Roques, F. A., Nuttall, W. J., & Newbery, D. M. (2006). Using probabilistic analysis to value power generation investments under uncertainty. University of Cambridge, Electricity Policy Research Group.
- Ross, S. A., Westerfield, R. W. ve Jaffe, J., 2010, Corporate Finance, Ninth Edition, ISBN 978-007-131308-7, NewYork. McGraw-Hill/Irwin.
- Simkins, B., & Simkins, R. (2013). Energy finance and economics: Analysis and valuation, risk management, and the future of energy (Vol. 606). John Wiley & Sons.
- Spinney, P. J., & Watkins, G. C. (1996). Monte Carlo simulation techniques and electric utility resource decisions. Energy Policy, 24(2), 155-163.
- TUREB, 2016, Türkiye Rüzgar Enerjisi İstatistik Raporu, http:// www.tureb.com.tr/files/yayinlar/temmuz_2016_istatistik.pdf (Erişim: 17.10.2016)
- Williams, S. K., Acker, T., Goldberg, M., ve Greve, M. (2008). Estimating the economic benefits of wind energy projects using Monte Carlo simulation with economic input/output analysis. Wind Energy, 11(4), 397-414.
- Cardell, J. B., & Anderson, C. L. (2010, January). Analysis of the system costs of wind variability through Monte Carlo simulation. In System Sciences (HICSS), 2010 43rd Hawaii International Conference on (pp. 1-8). IEEE.
Ayrıntılar
| Bölüm | Makaleler |
|---|---|
| Yazarlar | |
| Yayımlanma Tarihi | 1 Ekim 2017 |
| Gönderilme Tarihi | 3 Mart 2017 |
| Yayımlandığı Sayı | Yıl 2017 Sayı: 108 |
Cited By
TÜRKİYE’DE RÜZGÂR ENERJİSİNİN EKONOMİK BÜYÜME ÜZERİNDEKİ ETKİSİ: ARDL SINIR TESTİ YAKLAŞIMI
Akademik Araştırmalar ve Çalışmalar Dergisi (AKAD)
Başak Özarslan
https://doi.org/10.20990/kilisiibfakademik.437656
- Makale Dosyaları
Dergi özellikle maliye, finans ve bankacılık alanlarında faaliyet göstermektedir.