Capacity factor prediction and planning in the wind power generation industry

The common practice to calculate wind generation capacity values relies more on heuristic approximations than true system estimations. In this paper we proposed a more accurate method. In the first part of our analysis, a Monte Carlo simulation was created based on Markov chains to provide an independent estimate of the true behavior of wind farm capacity value as a function of system penetration. With this curve as a baseline, a technique for using beta distributions to model the input variables was adopted. A final step to increase accuracy involved the use of numerical convolution within the program to eliminate summation estimates.