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STTR Phase I: Matching the timing of renewable energy production with patterns of electricity demand

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0740001
Agency Tracking Number: 0740001
Amount: $150,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: EO
Solicitation Number: NSF 07-551
Timeline
Solicitation Year: N/A
Award Year: 2008
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
PO Box 1461 6920 Lupine Trail
Wilson, WY 83014
United States
DUNS: 608184714
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Edward Ladd
 MBA
 (307) 413-3333
 ted@dixonladd.com
Business Contact
 Edward Ladd
Title: MBA
Phone: (307) 413-3333
Email: ted@dixonladd.com
Research Institution
 University of Wyoming
 David Aadland
 
1000 E. University Ave.
Laramine, WY 82071 4800
United States

 (307) 766-4931
 Nonprofit College or University
Abstract

This Small Business Technology Transfer Phase I proposal we investigate the feasibility of a software application to search through public wind databases in order to match sites of renewable electricity production with sites of electricity demand. Renewable energy sources like wind and solar are intermittent, but still have clear diurnal and seasonal patterns. This tool will analyze historic data to these patterns with those of electricity consumption, producing recommendations to help electric utilities find specific wind sites that best coincide with their patterns of electric load. Similar analytical techniques are used in the financial industry but have yet to be applied to renewable energy supplies in an affordable package that can be effectively employed by non-statisticians. The team draws on experts from different arenas statistics, finance, software, marketing and the power industry and will collaborate with the University of Wyoming. If successful, this tool will have a market for commercialization throughout the country. Future plans include incorporation of data from other renewable sources, addition of complexities from constraints of transmission, and estimation of increases in monetary value. If deployed, the tool will reduce the impact of intermittency on our electricity system simply through statistical analysis and encourage construction of wind and solar farms throughout rural America. In addition to the commercial considerations, effective application of this tool will provide a path toward decreased reliance on fossil fuels.

* Information listed above is at the time of submission. *

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