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Rüzgâr Enerji Santrali Değerlemesinde Geleneksel Değerleme Yöntemi ile Monte Carlo Simülasyonu’nun Karşılaştırılması

Year 2022, , 995 - 1016, 15.12.2022
https://doi.org/10.31466/kfbd.1181990

Abstract

Günümüzde büyük bütçeli yatırımların değerlemesinde, geleneksel değerleme yöntemlerinden İndirgenmiş Nakit Akışları (İNA)’na göre hesaplanan Net Bugünkü Değer (NBD), hem literatürde ki akademik çalışmalarda hem de yatırım değerleme uygulamalarında sıklıkla kullanılmaktadır. Bir süredir yatırım değerlemede simülasyonlara, hesaplama kolaylığı ve daha dinamik bir çalışma prensibine sahip olmaları açısından oldukça fazla rastlanmaktadır. Monte Carlo Simülasyonu (MCS), simülasyon uygulamalarında en sık kullanılan yöntemlerin başında gelmektedir. MCS’yi diğer değerleme yöntemlerinden ayıran en önemli özelliği, çalışmaya konu olan parametrelerin direk değerlerinin kullanılması yerine her birine belirli bir aralıkta ve türde olasılık dağılımının tanımlanması ve optimal sonuca göre değil sistemin davranışını anlamaya yönelik olmasıdır. Bu çalışma da 2021 yılı Haziran ayında yatırıma başlanıldığı düşünülen ve proje parametrelerinin bu yılda hazırlanan ön fizibilite raporları ve piyasa verilerine göre öngörülerek belirlendiği, Sinop İlinde 5 MW elektrik üretim kapasiteli %35 rüzgâr kapasite faktörüne sahip bir Rüzgâr Enerji Santrali (RES) değerlendirilmiştir. Bu RES’in hem geleneksel yöntemlerden NBD ile hem de Crystal Ball programı kullanılarak MCS ile değerlemesi yapılmış olup, iki yöntem arasında ki sonuçlar birbirleri ile karşılaştırılarak değerlendirilmiştir.

References

  • Arıcı E. (2003). Optimal Capital Structure For Build-Operate-Transfer Power Projects. Yüksek Lisans Tezi, ODTÜ, Ankara.
  • Barroso, M. M. and Iniesta, J. B. (2014). A valuation of wind power projects in Germany using real regulatory options. Energy Journal, 77, 422-433.
  • Bendob, A. And Bentouir, N. (2019). Options Pricing by Monte Carlo Simulation, Binomail Tree and BMS Model: a comporative study of Nifty 50 options index. Journal of Banking and Financial Economics (pp:79-95). Warsaw, Poland.
  • Bilir, H. (2012). Enerji Yatırım Projelerinin Değerlendirilmesinde Reel Opsiyon Yaklaşımı. Ankara Üniversitesi, Sosyal Bilimler Enstitüsü Doktora Tezi, Ankara, pp.30.
  • Boomsma, T. K. and Linnerud, K. (2015). Market and policy risk under different renewable electricity suport schemes. Energy Journal, 89, 435-448.
  • Boomsma, T. K., Meade, N. and Fleten, S. E. (2012). Renewable energy investments under different support schemes: A real options approach. European Journal of Operational Research, 220, 225-237.
  • Brabazon, A. and O’Neill, M. (2009). Natural Computing in Computational Finance (Vol:2). New York, Springer.
  • Broyles, J. (2003). Financial Management and Real Options. John Wiley & Sons Ltd, England.
  • Cheah, C.Y.J. and Garvin, M. J. (2009). Application of Real Options in PPP Infrastructure Projects: Opportunities and Challenges. Policy, Finance &Management for Public- Private Partnership (Ch.13), Edited by A. Akintoye, and M. Beck,Wiley-Blackwell.
  • De Mare, G., Manganelli, B. and Nesticò, A. (2013). The Economiv Evaluation of Investments in The Energy Sector: A Model for The Optimization of the Scenario Analyses. Computational Science and Its Applications- ICCSA 2013, 359-374.
  • Graham, J. R. and Harvey, C. R. (2001). The Theory and Practice of Corporate Finance: Evidence from the Field. Journal of Financial Economics, 60, 187-243.
  • Guj, P. (2006). Mineral Project Evaluation – An Introduction, Philip Maxwell (der.). Australian Mineral Economics içinde, The Australian Institute of Mining and Metallurgy, Victoria.
  • Iniesta, J. B. and Barroso, M. M. (2015). Assessment of Offshore Wind Energy Project in Denmark. A Comparative Study with Onshore Projects Based on Regulatory Real Options. Journal of Solar Energy Engineering, 137(4): 041009 (13 pages).
  • Jog, V. M., and Srivastava, A. K. (1995). Capital Budgeting Practices in Corporate Canada. Financial Practice and Education, 5(2), 37-43.
  • Kodukula, P. and Papudesu, C. (2006). Project Valuation Using Real Options. Florida, ABD, J.Roos Publishing.
  • Malesevic, B. (2017). AADM next phase. Applicable Analysis and Discrete Mathematics, 11(1), 242-243.
  • Mun, J. (2006). Real Options Analysis Tools and Tecniques for Valuing Strategic Investments and Decisions, Second Edition, John Wiley & Sons, Inc., New Jersey.
  • Munoz, J. I., Contreras, J., Caamaño, J. and Correia, P. F. (2011). A decision-making tool for project investments based on real options: the case of wind power generation. Annals of Operations Research, 186, 465-490.
  • Onar, S. Ç. and Kılavuz, T. N. (2015). Risk Analysis of Wind Energy Investments in Turkey. Human and Ecological Risk Assesstment: An International Journal, 21, 1230-1245.
  • Reuter, W. H., Fuss, S., Szolgayova, J. and Obersteiner, M. (2012). Renewable energy investment: Policy and market impacts, 97, 249-254.
  • Rohlfs, W. and Madlener, R. (2014). Optimal investment strategies in power generation assets: The role of technological choice and exiting portfolios in the deployment of low-carbon technologies. International Journal of Greenhouse Gas Control, 28, 114-125.
  • Samıs, M. (2003). Applying Advanced Financial Methods (Real Options) to Mine Valuation Problems. MIRARCO Engineering Seminar Series, Kuiseb Minerals Consulting, Toronto.
  • SBB, 2020-2022 Dönemi Yatırım Programı Hazırlama Rehberi. https://www.sbb.gov.tr/wp-content/uploads/2019/10/2020 2022_Donemi_Yatirim_Programi_Hazirlama_Rehberi.pdf (01.10.2021).
  • Scatasta, S. and Mennel, T. (2009). Comparing Feed-In-Tariffs and Renewable Obligation Certificates- the Case of Wind Farming. Center for European Economic Research.
  • Schwartz, E. S. And Trigeorgis, L. (2004). Real Options and Investment under Uncertainty. London, England, The MIT Press.
  • Simkins, B., and Kemper, K. (2013). Real Options and Applicaitons in the Energy Industry. Chapter 11.
  • Sisodia, G.S., Soares, I. and Ferreira, P. (2016). Modeling business risk: the effect of regulatory revision on renewable energy investment- The Iberian case. Renewable Energy, 95, 303-313.
  • Sisodia, G.S., Soares, I., Ferreira, P., Banerji, S. and Prasad, R. (2015). Project Business Risk of Regulatory Change on Wind Power Project: Case of Spain.
  • Venetsanos, K., Angelopoulou, P. and Tsoutsos, T. (2002). Renewable energy sources project appraisal under uncertainty: the case of wind energy exploitation within a changing energy market environment. Energy Policy, 30, 293-307.
  • YEK Kanunu, Yenilenebilir Enerji Kaynaklarının Elektrik Enerjisi Üretimi Amaçlı Kullanımına İlişkin Kanun. https://www.mevzuat.gov.tr/MevzuatMetin/1.5.5346.pdf (25.09.2021).

Comparison of Traditional Valuation Method and Monte Carlo Simulation in Wind Power Plant Valuation

Year 2022, , 995 - 1016, 15.12.2022
https://doi.org/10.31466/kfbd.1181990

Abstract

Today, Net Present Value (NPV), which is calculated according to Discounted Cash Flows (DNA), which is one of the traditional valuation methods, is frequently used in the valuation of large-budget investments, both in academic studies in the literature and in investment valuation applications. Simulations, which have been used in investment valuation applications for a while, are quite common in terms of ease of calculation and having a more dynamic working principle. Monte Carlo Simulation (MCS) is one of the most frequently used methods in simulation applications. The most important feature that distinguishes MCS from other valuation methods is that instead of using the direct values of the parameters that are the subject of the study, the probability distribution is defined for each in a certain range and type, and it is aimed at understanding the behavior of the system, not according to the optimal result. In this study, a Wind Power Plant (RES) with a 5 MW electricity generation capacity and a wind capacity factor of 35% in the province of Sinop, which is thought to have started the investment market data prepared this year, was evaluated. This RES was evaluated both with NBD, which is one of the traditional methods, and with MCS using the Crystal Ball program, and the results between the two methods were evaluated by comparing them with each other.

References

  • Arıcı E. (2003). Optimal Capital Structure For Build-Operate-Transfer Power Projects. Yüksek Lisans Tezi, ODTÜ, Ankara.
  • Barroso, M. M. and Iniesta, J. B. (2014). A valuation of wind power projects in Germany using real regulatory options. Energy Journal, 77, 422-433.
  • Bendob, A. And Bentouir, N. (2019). Options Pricing by Monte Carlo Simulation, Binomail Tree and BMS Model: a comporative study of Nifty 50 options index. Journal of Banking and Financial Economics (pp:79-95). Warsaw, Poland.
  • Bilir, H. (2012). Enerji Yatırım Projelerinin Değerlendirilmesinde Reel Opsiyon Yaklaşımı. Ankara Üniversitesi, Sosyal Bilimler Enstitüsü Doktora Tezi, Ankara, pp.30.
  • Boomsma, T. K. and Linnerud, K. (2015). Market and policy risk under different renewable electricity suport schemes. Energy Journal, 89, 435-448.
  • Boomsma, T. K., Meade, N. and Fleten, S. E. (2012). Renewable energy investments under different support schemes: A real options approach. European Journal of Operational Research, 220, 225-237.
  • Brabazon, A. and O’Neill, M. (2009). Natural Computing in Computational Finance (Vol:2). New York, Springer.
  • Broyles, J. (2003). Financial Management and Real Options. John Wiley & Sons Ltd, England.
  • Cheah, C.Y.J. and Garvin, M. J. (2009). Application of Real Options in PPP Infrastructure Projects: Opportunities and Challenges. Policy, Finance &Management for Public- Private Partnership (Ch.13), Edited by A. Akintoye, and M. Beck,Wiley-Blackwell.
  • De Mare, G., Manganelli, B. and Nesticò, A. (2013). The Economiv Evaluation of Investments in The Energy Sector: A Model for The Optimization of the Scenario Analyses. Computational Science and Its Applications- ICCSA 2013, 359-374.
  • Graham, J. R. and Harvey, C. R. (2001). The Theory and Practice of Corporate Finance: Evidence from the Field. Journal of Financial Economics, 60, 187-243.
  • Guj, P. (2006). Mineral Project Evaluation – An Introduction, Philip Maxwell (der.). Australian Mineral Economics içinde, The Australian Institute of Mining and Metallurgy, Victoria.
  • Iniesta, J. B. and Barroso, M. M. (2015). Assessment of Offshore Wind Energy Project in Denmark. A Comparative Study with Onshore Projects Based on Regulatory Real Options. Journal of Solar Energy Engineering, 137(4): 041009 (13 pages).
  • Jog, V. M., and Srivastava, A. K. (1995). Capital Budgeting Practices in Corporate Canada. Financial Practice and Education, 5(2), 37-43.
  • Kodukula, P. and Papudesu, C. (2006). Project Valuation Using Real Options. Florida, ABD, J.Roos Publishing.
  • Malesevic, B. (2017). AADM next phase. Applicable Analysis and Discrete Mathematics, 11(1), 242-243.
  • Mun, J. (2006). Real Options Analysis Tools and Tecniques for Valuing Strategic Investments and Decisions, Second Edition, John Wiley & Sons, Inc., New Jersey.
  • Munoz, J. I., Contreras, J., Caamaño, J. and Correia, P. F. (2011). A decision-making tool for project investments based on real options: the case of wind power generation. Annals of Operations Research, 186, 465-490.
  • Onar, S. Ç. and Kılavuz, T. N. (2015). Risk Analysis of Wind Energy Investments in Turkey. Human and Ecological Risk Assesstment: An International Journal, 21, 1230-1245.
  • Reuter, W. H., Fuss, S., Szolgayova, J. and Obersteiner, M. (2012). Renewable energy investment: Policy and market impacts, 97, 249-254.
  • Rohlfs, W. and Madlener, R. (2014). Optimal investment strategies in power generation assets: The role of technological choice and exiting portfolios in the deployment of low-carbon technologies. International Journal of Greenhouse Gas Control, 28, 114-125.
  • Samıs, M. (2003). Applying Advanced Financial Methods (Real Options) to Mine Valuation Problems. MIRARCO Engineering Seminar Series, Kuiseb Minerals Consulting, Toronto.
  • SBB, 2020-2022 Dönemi Yatırım Programı Hazırlama Rehberi. https://www.sbb.gov.tr/wp-content/uploads/2019/10/2020 2022_Donemi_Yatirim_Programi_Hazirlama_Rehberi.pdf (01.10.2021).
  • Scatasta, S. and Mennel, T. (2009). Comparing Feed-In-Tariffs and Renewable Obligation Certificates- the Case of Wind Farming. Center for European Economic Research.
  • Schwartz, E. S. And Trigeorgis, L. (2004). Real Options and Investment under Uncertainty. London, England, The MIT Press.
  • Simkins, B., and Kemper, K. (2013). Real Options and Applicaitons in the Energy Industry. Chapter 11.
  • Sisodia, G.S., Soares, I. and Ferreira, P. (2016). Modeling business risk: the effect of regulatory revision on renewable energy investment- The Iberian case. Renewable Energy, 95, 303-313.
  • Sisodia, G.S., Soares, I., Ferreira, P., Banerji, S. and Prasad, R. (2015). Project Business Risk of Regulatory Change on Wind Power Project: Case of Spain.
  • Venetsanos, K., Angelopoulou, P. and Tsoutsos, T. (2002). Renewable energy sources project appraisal under uncertainty: the case of wind energy exploitation within a changing energy market environment. Energy Policy, 30, 293-307.
  • YEK Kanunu, Yenilenebilir Enerji Kaynaklarının Elektrik Enerjisi Üretimi Amaçlı Kullanımına İlişkin Kanun. https://www.mevzuat.gov.tr/MevzuatMetin/1.5.5346.pdf (25.09.2021).
There are 30 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Duygu Bıyıklı 0000-0002-0220-5101

Faik Ahmet Sesli 0000-0001-8352-734X

Pelin Kasap 0000-0002-1106-710X

Publication Date December 15, 2022
Published in Issue Year 2022

Cite

APA Bıyıklı, D., Sesli, F. A., & Kasap, P. (2022). Rüzgâr Enerji Santrali Değerlemesinde Geleneksel Değerleme Yöntemi ile Monte Carlo Simülasyonu’nun Karşılaştırılması. Karadeniz Fen Bilimleri Dergisi, 12(2), 995-1016. https://doi.org/10.31466/kfbd.1181990