A new merit function to accommodate high wind power penetration of WGRs (wind generating resources)

J. Hur and R. Baldick

Energy, 2016, vol. 108, issue C, 34-40

Abstract: In this paper, we propose a new merit function to provide practical information to find optimal wind farm locations and projects based on spatial wind farm output prediction, including correlation with other wind farms. Our approach can predict what will happen when a new wind farm is added at various locations. Spatial power prediction of geographically distributed wind farms and their statistics through the proposed prediction model based on Kriging techniques will be presented. Using the proposed prediction model of wind generating resources, the performance of the spatial merit function in the context of the McCamey areas of ERCOT (Electric Reliability Council of Texas) will be provided. A new merit function through the prediction of wind farm outputs can play a key role to accommodate high wind power penetration from spatially distributed wind farms in power system planning models. In addition, we also propose the Kriged Wind Farm-SMES (Superconducting Magnetic Energy Storage System) hybrid model to enhance the higher wind power penetration levels using a new merit function. The proposed merit function requires only the existing data of wind generating resources around the candidate wind farm sites in order to reduce the time and costs for the installation of an anemometry tower as a practical method of wind resource assessment study compared to MCP (Measure-Correlate-Predict).

Keywords: Merit function; Wind farm sites; Wind farm output prediction; Spatial analysis; Kriging techniques; Kriged Wind Farm-SMES hybrid model (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544215016217
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:108:y:2016:i:c:p:34-40

DOI: 10.1016/j.energy.2015.11.058

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().