Bayesian Persistence Analysis for Wind Energy

by Harish G. Rao, (A.M.ASCE), Asst. Prof.; Dept. of Civ. Engrg., Old Dominion Univ., Norfolk, Va. 23508,
Ross B. Corotis, (M.ASCE), Prof. and Head of Civ. Engrg.; Dept. of Civ. Engrg./Materials Sci. and Engrg., The Johns Hopkins Univ., Baltimore, Md. 21218,

Serial Information: Journal of the Energy Division, 1982, Vol. 108, Issue 2, Pg. 116-127

Document Type: Journal Paper

Abstract: The persistence of wind speed is an important consideration in the assessment of a wind enery conversion site. Since data are often limited at such a site, a practical Bayesian formulation is presented whereby regional and site-specific mean wind speed may be used to calibrate a probability model of persistence. Prior estimates for the principal model parameter are obtained from the ratio of wind speed level considered for persistence to site mean wind speeds using weighted regression. The Bayesian approach is in terms of specific persistence events, such as a wind speed run above a given wind speed exceeding a particular duration. Updating may be through an improved estimate of the site mean wind speed or, if available, a site persistence analysis.

Subject Headings: Wind speed | Bayesian analysis | Site investigation | Data processing | Wind power | Calibration | Probability | Parameters (statistics) |

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