Risk analysis methodologies for financial evaluation of wind energy power generation projects in the Brazilian system

This paper presents two methodologies for financial analysis of wind energy power plants, explicitly considering uncertainties associated to wind speeds. The first one employs Monte Carlo simulation (MCS) and the second make use of the Box and Jenkins (B&J) approach to time series analysis. These methodologies were used to generate synthetic sequences of wind speeds, from a sample of wind speeds series obtained in a specific site in Brazil. The MCS is based on random choices of a variable with a specific probability distribution. The B&J methodology used in this study assumes that the residual of a seasonally adjusted wind speed series is generated by the combination of auto regressive and moving-average processes. The sample values obtained in either methodology constitutes a random scenario, for which a financial analysis-performed with the aid of the software ANAFIN, developed by CEPEL and ELETROBRAS-is accomplished. Financial indicators for each scenario are obtained in order to get empirical probability distributions to be used in the financial risk analysis of the wind power project. The results of the risk analysis are compared to those of traditional (deterministic) analysis, in terms of expected values of financial indicators, as for instance the internal rate of return (IRR) and the net present value (NPV). The empirical probability distributions are also used to calculate risk measures such as the probability of negative returns.