Integration of Monte Carlo Risk Simulation into Cash Flow Optimization Processes : a case study in wind energy project

Abstract

The financial success of wind energy projects depends mainly on effective cash flow management, especially under market and environmental uncertainties. This research develops a practical simulation model based on Excel to illustrate the problem of financial risk management in such projects. The research objective is to present a simple and implementable modelling framework that can model the uncertainty in the cash flow forecasting process to help make better decisions during the project planning phase.

This study is based on project finance and risk management concepts, especially cash flow management, Monte Carlo simulation, and wind energy economics. A quantitative modelling based on probability distributions was developed using Microsoft Excel and Crystal Ball, where realistic parameters such as Weibull distributions with wind speed, energy unit price, installation cost, and energy production levels were used.

By implementing a Monte Carlo simulation, instead of providing a single estimate, a range of results can be obtained that clearly understand the impact of uncertain variables on NPV. Sensitivity and reliability analyses allow project managers to identify important financial variables, especially risk centres. This simulation model is proven to be helpful in financial planning, reducing uncertainty, and increasing the reliability of investment decisions.