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

Conference · Wed Nov 14 04:00:00 EST 2018

OSTI ID:1482898

Optis, Michael ^[1]

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1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)

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.

• Research Organization: National Renewable Energy Laboratory (NREL), Golden, CO (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
• DOE Contract Number: AC36-08GO28308
• OSTI ID: 1482898
• Report Number(s): NREL/PO-5000-72233
• Country of Publication: United States
• Language: English

Related Subjects

17 WIND ENERGY
29 ENERGY PLANNING, POLICY, AND ECONOMY
Monte Carlo
annual energy production
reanalysis
uncertainty
wind power