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

Stefan Wieke

doi:10.22630/srees.9798

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Published:

Oct 23, 2024

Issue

Online First

Section

Original papers

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Stefan Wieke

Mendel University, Faculty of Business and Economics, Czech Republic

DOI: https://doi.org/10.22630/srees.9798

Keywords : decision making, life cycle cost analysis, case studies, risk mitigation, Monte Carlo simulation, energy cost

Abstract

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.

How to Cite

Wieke, S. (2024). Life cycle cost analysis in investment projects – examination of case studies and risk mitigation with Monte Carlo simulation . Scientific Review Engineering and Environmental Sciences (SREES), 1–14. https://doi.org/10.22630/srees.9798

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