JSM 2005 Online Program

Abstract #304282

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	74
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 8:00 PM to 9:50 PM
Sponsor:	Section on Statistics and the Environment
Abstract - #304282
Title:	On the Relationship between Wind Speeds at Neighboring Locations
Author(s):	John Rogers*+ and Anthony Rogers
Companies:	Westat and University of Massachusetts
Address:	1650 Research Blvd, Rockville, MD, 20850, United States
Keywords:	Time series ; Wind speed ; Measure-Correlate-Predict ; Wind resource estimation ; MCP
Abstract:	In order to estimate the potential benefit of the generation of electricity by wind, MCP (Measure-Correlate-Predict) procedures attempt to predict the wind speed at a "target" location from longterm historical wind speeds at a neighboring "reference" location. Traditionally, a linear relationship between the target and reference site wind speeds is assumed within wind direction sectors. This approach does not account for serial correlation, seasonal effects, and daily variation. This research modeled the mean and standard deviation of the east-west and north-south wind components at neighboring locations using weighted ARMA(1,1) models with seasonal and daily terms. The wind direction differences were modeled using additional directional terms. The residual wind components at the reference and target sites are assumed to follow a linear measurement error model. This paper discusses the model and how well it fits the winds using data from four pairs of neighboring sites. The model appears to provide an improved fit, particularly when wind differences between the two sites are a function of time.

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