Life cycle cost analysis in investment projects – examination of case studies and risk mitigation with Monte Carlo simulation

• Autorzy: Wieke Stefan

Identyfikatory

DOI

10.22630/srees.9798

• Języki publikacji: EN

Abstrakty

EN

This work focuses on life cycle cost (LCC) analysis in the German natural gas infrastructure and recommends strategies to mitigate the uncertainties and risks involved using Monte Carlo simulation (MCS). It deals with the impact of input data and predicting the future development of input data on the results of the LCC analysis and discusses MCS for risk mitigation. Seven case studies for investments in Germany’s natural gas infrastructure are analyzed. In addition to the executed case studies, a case study from a scientific journal is included. The case studies were conducted between 2005 and 2015. Evaluation with real historical input data shows that the results of an LCC analysis depend on the reliability of input data and predictions on their development. The retrospective view shows that the best options are not always identified. Therefore, the results need to be validated using risk-mitigation methods, such as MCS. The executed case studies reflect the opinions of experts. This work shows how risk is mitigated through MCS while focusing on LCC analysis in the German natural gas infrastructure; however, the proposed risk mitigation with MCS can be adopted for other investment projects comprising capital expenditure (CAPEX) and operational expenditure (OPEX), for example, in construction, machines and other fields.

Słowa kluczowe

EN

decision making; life cycle cost analysis; case studies; risk mitigation; Monte Carlo simulation; energy cost

• Wydawca: Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
• Czasopismo: Przegląd Naukowy Inżynieria i Kształtowanie Środowiska
• Rocznik: 2025
• Tom: Vol. 34, No. 1
• Strony: 3--18
• Opis fizyczny: Bibliogr. 24 poz., wykr.

Twórcy

autor

Wieke Stefan

• Mendel University, Faculty of Business and Economics, Czech Republic

• https://orcid.org/0000-0001-6875-5053

Bibliografia

• Ally, J., & Pryor, T. (2016). Life cycle costing of diesel, natural gas, hybrid and hydrogen fuel cell bus systems: an Australian case study. Energy Policy, 94, 285–294. https://doi.org/10.1016/j.enpol.2016.03.039
• Choudhry, M. (2013). An introduction to value-at-risk. John Wiley & Sons.
• Cierniak, S. (2001). Life cycle-costs von Kolben- und Turbokompressoren. Erdöl, Erdgas, Kohle, 117 (11), 511–517.
• Deutsches Institut für Normung [DIN]. (2012). Betriebswirtschaftliche Berechnungen für Investitionsgüter und Anlagen [Economy calculation systems for capital goods and plants] (VDI 6025:2012-11).
• Elfarra, M. A. & Kaya, M. (2021). Estimation of electricity cost of wind energy using Monte Carlo simulations based on nonparametric and parametric probability density functions. Alexandria Engineering Journal, 60 (4), 3631–3640. https://doi.org/10.1016/j.aej.2021.02.027
• Gleißner, W., & Wolfrum, M. (2019). Grundlagen des Risikomanagements. In Risikoaggregation und Monte-Carlo-Simulation (pp. 3–13). Springer. https://doi.org/10.1007/978-3-658-24274-9_2
• Heck, N., Smith, C., & Hittinger, E. (2016). A Monte Carlo approach to integrating uncertainty into the levelized cost of electricity. Electricity Journal, 29 (3), 21–30. https://doi.org/10.1016/j.tej.2016.04.001
• Heyer, F., & Wieke, S. (1998). Verdichter und Antriebsmaschinen für die Erdgasspeicherung und den Erdgastransport - Auswahl unter technischen und wirtschaftlichen Aspekten [Selection of compressors and drives for storage and transport of natural gas - technical and economical aspects]. Erdoel Erdgas Kohle, 114, 548–551.
• Homann, K., Klocke, B., Hüwener, T. & Wernekinck, U. (2017). Handbuch der Gasversorgungstechnik. DIV Deutscher Industrieverlag.
• Ilg, P., Scope, C., Muench, S., & Guenther, E. (2017). Uncertainty in LCC for long-range infrastructure. Part I leveling the playing field to address uncertainties. International Journal Life Cycle Assess, 22, 277–292. https://doi.org/10.1007/s11367-016-1154-1
• International Organization for Standardization [ISO]. (2000). Petroleum and natural gas industries - Life cycle costing. Part 1: Methodology (EN ISO 15663-1).
• International Organization for Standardization [ISO]. (2001a). Petroleum and natural gas industries - Life cycle costing. Part 2: Guidance on application of methodology and calculation methods (EN ISO 15663-2).
• International Organization for Standardization [ISO]. (2001b). Petroleum and natural gas industries - Life cycle costing. Part 3: Implementation guidelines (EN ISO 15663-3).
• Jorion, P. (2002). How informative are value‐at‐risk disclosures? The Accounting Review, 77 (4), 911–931. https://doi.org/10.2308/ACCR.2002.77.4.911
• Kawauchi, Y., & Rausand, M. (1999). Life Cycle Cost (LCC) analysis in oil and chemical process industries. Toyo Engineering Corp. https://www.researchgate.net/publication/228594034_Life_Cycle_Cost_LCC_Analysis_in_Oil_and_Chemical_Process_Industries
• Korpi, E., & Ala-Risku, T. (2008). Life cycle costing: A review of published case studies. Managerial Auditing Journal, 23 (3), 240–261. https://doi.org/10.1108/02686900810857703
• Lee D. B., Jr (2002). Fundamentals of life-cycle cost analysis. Transportation Research Record, 1812 (1), 203–210. https://doi.org/10.3141/1812-25
• Nábrádi, A., & Szöllösi, L. (2007). Key aspects of investment analysis. APSTRACT: Applied Studies in Agribusiness and Commerce, 1 (1), 53–56. https://doi.org/10.22004/ag.econ.43577
• Rahman, S., & Vanier, D. J. (2004). Life cycle cost analysis as a decision support tool for managing municipal infrastructure. CIB 2004 triennial congress, 2 (1), 11–8. https://www.irb.fraunhofer.de/CIBlibrary/search-quick-result-list.jsp?A&idSuche=CIB+DC9737
• Scope, C., Ilg, P., Muench, S., & Guenther, E. (2016). Uncertainty in life cycle costing for long-range infrastructure. Part II: guidance and suitability of applied methods to address uncertainty. The International Journal of Life Cycle Assessment, 21, 1170–1184. https://doi.org/10.1007/s11367-016-1086-9
• Shafiee, M., Animah, I., Alkali, B., & Baglee, D. (2019). Decision support methods and applications in the upstream oil and gas sector. Journal of Petroleum Science and Engineering, 173, 1173–1186. https://doi.org/10.1016/j.petrol.2018.10.050
• Tat, A. N. (2018). Electricity price forecasting using Monte Carlo simulation: the case of Lithuania. Ekonomika, 97 (1), 76–86. https://doi.org/10.15388/Ekon.2018.1.11780
• Wealer, B., Bauer, S., Hirschhausen, C. V., Kemfert, C., & Göke, L. (2021). Investing into third generation nuclear power plants – Review of recent trends and analysis of future investments using Monte Carlo Simulation. Renewable and Sustainable Energy Reviews, 143, 110836. https://doi.org/10.1016/j.rser.2021.110836
• XLRisk. https://github.com/pyscripter/XLRisk [accessed: 14.09.2024].