A Monte Carlo-Based Approach to Assessing Annual Energy Production and Uncertainty

The industry standard approach to assessing annual energy production (AEP) uncertainty can be limited because of the assumption of uncorrelated uncertainty categories and subjectivity in calculations. A Monte Carlo approach to uncertainty quantification can largely overcome these limitations and provide a more robust assessment of energy uncertainty. Here, we demonstrate the Monte Carlo approach in the context of AEP estimation using operational data. Monthly net energy production for all reporting wind power plants in the United States was taken from the Energy Information Administration (EIA) 923 database. Atmospheric data from three reanalysis products were also considered. After filtering for wind plants that had at least 8 months of data and moderate-to-strong correlation with all three reanalysis products (R2 > 0.6), we assessed 472 wind power plants total.