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

Abstract

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.

Authors:
 [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
OSTI Identifier:
1482898
Report Number(s):
NREL/PO-5000-72233
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the AWEA Wind Resource & Project Energy Assessment Conference 2018, 11-12 September 2018, Austin, Texas
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY; wind power; Monte Carlo; uncertainty; reanalysis; annual energy production

Citation Formats

Optis, Michael. A Monte Carlo-Based Approach to Assessing Annual Energy Production and Uncertainty. United States: N. p., 2018. Web.
Optis, Michael. A Monte Carlo-Based Approach to Assessing Annual Energy Production and Uncertainty. United States.
Optis, Michael. Wed . "A Monte Carlo-Based Approach to Assessing Annual Energy Production and Uncertainty". United States. doi:. https://www.osti.gov/servlets/purl/1482898.
@article{osti_1482898,
title = {A Monte Carlo-Based Approach to Assessing Annual Energy Production and Uncertainty},
author = {Optis, Michael},
abstractNote = {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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Nov 14 00:00:00 EST 2018},
month = {Wed Nov 14 00:00:00 EST 2018}
}

Conference:
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