of them having only a single sampling performed (i.e., either revenue meter, reference wind speed data, IAV, linear regression, or windiness correction). For each component, we run the Monte Carlo simulation 10,000 times. We quantify the impact of each single uncertainty component on the long-term operational AEP in terms of the coefficient of variation of the distribution of operational AEP resulting from the Monte Carlo simulation run. Convergence of the AEP distribution within 0.5% of the true mean after the 10,000 Monte Carlo runs was verified for all projects, with 95% confidence.

The code used to perform the AEP calculations is published and documented in NREL’s open-source operational assessment software, OpenOA.[^2] Calculations were performed on Eagle, NREL’s high-performance computing cluster. Specifically, each wind plant was assigned a different processor and run in parallel. Given the general simplicity of the AEP method used here, computational requirements were moderate despite the 50,000 simulations (10,000 runs x 5 uncertainty setups) required for each wind plant.

Combination of Uncertainty Components
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Once the contribution from each uncertainty component to the long-term operational AEP uncertainty has been quantified, the different components need to be combined to obtain the total AEP uncertainty. As stated in the 