Correlation and statistical characteristics of aggregate wind power in large transcontinental systems
Article first published online: 6 FEB 2013
Copyright © 2013 John Wiley & Sons, Ltd.
Volume 17, Issue 6, pages 793–810, June 2014
How to Cite
Louie, H. (2014), Correlation and statistical characteristics of aggregate wind power in large transcontinental systems. Wind Energ., 17: 793–810. doi: 10.1002/we.1597
- Issue published online: 10 APR 2014
- Article first published online: 6 FEB 2013
- Manuscript Accepted: 26 DEC 2012
- Manuscript Revised: 11 NOV 2012
- Manuscript Received: 23 DEC 2011
- geographic diversity;
- wind energy;
- wind plant integration;
- wind power generation
Studies have shown that the unpredictability and variability of wind power is reduced in systems with large numbers of geographically diverse wind plants. These effects are caused by the decreased correlation of power output between wind plants as their separation and diversity in terrain increases. One way that system operators have increased geographic diversity is by enlarging balancing areas through the physical or administrative connection of adjacent systems. This strategy can be extended from the regional level to the transcontinental level. As such, it is important to study the correlation and statistical characteristics of aggregate wind power between large, distant systems. This paper analyzes multi-year historical data from four North American system operators—Bonneville Power Administration, Electric Reliability Council of Texas, Midwest Independent Transmission System Operator and PJM—to see how effective transcontinental interconnection of systems is at enabling wind plant integration. The effects of separation and timescale on correlations of instantaneous and hourly variations are analyzed. The analysis is complemented by a study of a hypothetical transcontinental connection of the systems across yearly, monthly, daily and hourly timescales. The results show that correlations between large systems exhibit similar characteristics as the correlations between individual wind plants, but are somewhat larger in magnitude. The transcontinental system exhibits a close to normal distribution of power output and decreased variability, but there is still appreciable and statistically significant correlation at the longer timescales driven by seasonal and diurnal forcing, as well as synoptic weather systems. Copyright © 2013 John Wiley & Sons, Ltd.