LIFE CYCLE COST OF BIOMASS POWER PLANT - MONTE CARLO SIMULATION OF INVESTMENT
DOI:
https://doi.org/10.5937/ekoPolj1702587OKeywords:
life cycle cost, simulation, variation, discounting.Abstract
Assessment of life cycle cost is considered as an important instrument for designing and evaluating success of every project. The aim of this work is to determine the precise impact of the investment costs and future operating and maintenance costs of CHP biomass plant. By using the Monte Carlo simulation are determined variations in the settings and the possible impact on the investment risk. The results show that the investment is justifed, thanks to the positive outcome of the net present value (NPV), internal rate of return (IRR) and the payback period. The greatest impact on the variability of annual profts have operating costs, which have the highest coefficient of variation of 6.44% and the largest share. Variability of net present value of 4% is acceptable, and the investment is considered as stable.
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References
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3. Castillo-Villar, K. K., Eksioglu, S., Taherkhorsand, M. (2017): Integrating biomass quality variability in stochastic supply chain modeling and optimization for largescale biofuel production. Journal of Cleaner Production, vol. 149, p. 904-918. USA.
4. Clark, V., Reed, M., Stephan, J.(2010): Using Monte Carlo Simulation for a Capital Budgeting Project. Management accounting quarterly, vol 12, No 1, p. 21, USA.
5. Glassley, W. (2011): Renewable energy and the environmental, Book. p.252
6. Hertz, David B. (1979): Risk Analysis in Capital Investment. Harvard Business Review, USA.
7. Iglinski, B., Buczkowski R., Iglinska A., Cichosz M., Piechota G., Kujawski W. (2012): Agricultural biogas plants in Poland: Investment process, economical and environmental aspects,biogas potential, Renewable and sustainable energy reviews vol. 16, p. 4890–4900, Toruń, Poland.
8. International Energy Agency. (2007): Biomass for Power Generation and CHP. p.4 Available at: www.iea.org/publications/freepublications/publication/essentials3.pdf
9. Kaufman, R., J. (1970): Life cycle costing: a decision-making tool for capital equipment acquision, Cost and Management. USA.
10. Korn, R., Korn, E., Kroisandt, G. (2011): Monte Carlo methods and models in fnance and insurance. Annals of Actuarial Science, vol. 5, No. 2, p 303-304. Chapman&Hall Book, New York, USA.
11. Metropolis, N., Ulam, S. (1949): The Monte Carlo Method. Journal of the American statistical association. vol. 44, USA.
12. Milic, D. (2015): Doktorska disertacija. Metode vrednovanja poljoprivrednog zemljišta. Poljoprivredni fakultet, Novi Sad, Srbija.
13. Milic, D. (2009): Magistarsta teza. Procena vrednosti kapitala poljoprivrednog preduzeća primenom prinosne metode, Poljoprivredni fakultet, Novi Sad, Srbija.
14. Munitlak, O., Ivanovic, Penezic, N. (2005): Ekonomski instrumenti u funkciji eksternih efekata. Životna sredina ka Evropi. Fakultet za preduzetni menadžment. p.228-232., Novi Sad, Srbija.
15. Pedraza, J., M. (2015): Electrical energy generation in Europe. The current situation and pespective in the use of renewable energy sources and nuclear power for regional electricity generation. Book. ISBN 978-3-319-16082-5. Vienna, Austria.
16. Princiotta, F., T. (2011): Global climate change – the technology challenge. Book. US Environmental Protection Agency, USA.
17. U.S. Department of Energy (2016): Biomass for electricity generation. Federal Energy Management Program (FEMP), USA. www.wbdg.org/resources/biomasselectricity-generation
18. Vlada Republike Srbije (2016): Uredba o podsticajnim merama za proizvodnju električne energije iz obnovljivih izvora i iz visokoefkanse kombinovane proizvodnje električne i toplotne energije, Beograd, Srbija.
19. Walla, C., Schneeberger, W. (2008): The optimal size for biogas plants, Biomass and bioenergy, vol 32, p.551-557, Vienna, Austria.
20. Yu, S., Tao, J. (2008): Life cycle simulation-based economic and risk assessment of biomass-based fuel ethanol (BFE) projects in different feedstock planting areas. Energy. Science Direct, Elsevier, vol. 33, p. 375-384, Shanghai, PR China.
21. Zekic, V., Tica, N., Tomovic, V., Milic D.(2014): Predviđanje ekonomskih parametara u svinjarstvu primenom simulacionih metoda. Letopis naucnih radova, vol. 38, broj I, p. 125, Novi Sad, Srbija.
22. Produktna berza, www.proberza.co.rs, december 2016.
23. Sistem tržišnih informacija Republike Srbije (STIPS), www.stips.minpolj.gov.rs/stips/detaljni, june-december 2016.
24. Republicki zavod za statistiku, www.stat.gov.rs , Saopštenja CN11, CN22, ZP14, december 2016.
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Published
2017-06-30
How to Cite
Odavić, P., Zekić, V., & Milić, D. (2017). LIFE CYCLE COST OF BIOMASS POWER PLANT - MONTE CARLO SIMULATION OF INVESTMENT. Economics of Agriculture, 64(2), 587–599. https://doi.org/10.5937/ekoPolj1702587O
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Original scientific papers
