A stochastic model to analyze the economic competitiveness of wind power projects within a restructured electricity industry

This paper describes a Net Present Value (NPV) model based on probability distributions to assess the financial returns of the small wind power projects with special emphasis in homeowner projects. The probability distributions were employed to reproduce the stochastic behavior of wind power generation, spot market, retail prices, household energy consumption and CO
₂
allowances trading. The proposed model was built in crystal ball software and the simulations were performed using Monte Carlo techniques. In our model, we applied two different mechanisms to support renewable energy development: the environmental benefits associated to the sale of the carbon credits and the incentives derived from the governmental grants. In windy locations or high wind turbine capacity, the simulation results revealed that the use of the environmental benefits in the NPV calculation is more profitable than the governmental grants, allowing renewable energy technologies to compete with conventional power production. Nonetheless, it has been shown that in less windy location, the small wind power projects are still depending on the governmental support. Moreover, the sensitivity analysis demonstrated the importance of the clear and consistent mechanisms to compensate the customers who sell and deliver their excess generation to the electric grid.