Uncertainty Analysis in MCP-Based Wind Resource Assessment and Energy Production Estimation
Author(s) -
Matthew A. Lackner,
Anthony Rogers,
James F. Manwell
Publication year - 2008
Publication title -
journal of solar energy engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.55
H-Index - 83
eISSN - 1528-8986
pISSN - 0199-6231
DOI - 10.1115/1.2931499
Subject(s) - weibull distribution , wind resource assessment , wind power , uncertainty analysis , wind speed , turbine , resource (disambiguation) , sensitivity analysis , production (economics) , estimation , sensitivity (control systems) , environmental science , computer science , reliability engineering , meteorology , statistics , engineering , wind direction , simulation , mathematics , economics , systems engineering , mechanical engineering , computer network , physics , electronic engineering , electrical engineering , macroeconomics
This paper presents a mathematical framework to properly account for uncertainty in wind resource assessment and wind energy production estimation. A meteorological tower based wind measurement campaign is considered exclusively, in which measure-correlate-predict is used to estimate the long-term wind resource. The evaluation of a wind resource and the subsequent estimation of the annual energy production (AEP) is a highly uncertain process. Uncertainty arises at all points in the process, from measuring the wind speed to the uncertainty in a power curve. A proper assessment of uncertainty is critical for judging the feasibility and risk of a potential wind energy development. The approach in this paper provides a framework for an accurate and objective accounting of uncertainty and, therefore, better decision making when assessing a potential wind en-ergy site. It does not investigate the values of individual uncertainty sources. Three major aspects of site assessment uncertainty are presented here. First, a method is presented for combining uncertainty that arises in assessing the wind resource. Second, methods for handling uncertainty sources in wind turbine power output and energy losses are pre-sented. Third, a new method for estimating the overall AEP uncertainty when using a Weibull distribution is presented. While it is commonly assumed that the uncertainty in the wind resource should be scaled by a factor between 2 and 3 to yield the uncertainty in the AEP, this work demonstrates that this assumption is an oversimplification and also presents a closed form solution for the sensitivity factors of the Weibull parameters. DOI: 10.1115/1.2931499
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