Prioritization of risk events in PPP wind power projects using integrated FMEA and Monte Carlo simulation

Abstract

The popularity of public private partnership (PPP) projects has grown all over the world, especially in developing countries. The success of PPP projects heavily depends on how effectively risk assessments are performed. Failure Mode and Effects Analysis (FMEA) enables risk assessment by considering the impact, the probability, and the detection rate of risk events. However, it is very difficult to predict a single value for these variables. The objective of this research is to integrate FMEA and Monte Carlo simulation, and to use this model to perform risk assessment and prioritization of risks in PPP projects. The proposed model was applied to a real wind power generation investment located in the Aegean region of Turkey. The top three important risk events are "unfavorable wind speed", "fluctuation in exchange rates", and "interest rate volatility". The model perfumed to the satisfaction of experts. The primary contributions of this research include (1) a method that allows the identification of the risk events in PPP projects; (2) a model that performs risk assessment and prioritization of risk events in PPP projects; (3) an integrated FMEA and Monte Carlo simulation model that performs stochastic risk assessment in PPP projects. Both public agencies and private consortia should benefit from the proposed model.