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

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

By: Stefan WiekeORCID  
Open Access
|Oct 2024

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.

DOI: https://doi.org/10.22630/srees.9798 | Journal eISSN: 2543-7496 | Journal ISSN: 1732-9353
Language: English
Page range: 3 - 18
Submitted on: May 9, 2024
Accepted on: Sep 16, 2024
Published on: Oct 23, 2024
Published by: Warsaw University of Life Sciences - SGGW Press
In partnership with: Paradigm Publishing Services

© 2024 Stefan Wieke, published by Warsaw University of Life Sciences - SGGW Press
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.