Analytics for Renewable Energy
Schedule
This project will formally commence
on January 1, 2008 and conclude on
December 31, 2008 with a report to
the National Science Foundation.
This project will formally commence
on January 1, 2008 and conclude on
December 31, 2008 with a report to
the National Science Foundation.
Team Members
- Ted Ladd, team leader
- Crile Carvy, software
- Professor David Aadland, statistics
- Ross Manley, research
- Ben Ellis, business development
- Ted Ladd, team leader
- Crile Carvy, software
- Professor David Aadland, statistics
- Ross Manley, research
- Ben Ellis, business development
Funding
This project is supported by a SBIR
Phase I grant from the National
Science Foundation, along with
private investment from Ladd Energy.
This project is supported by a SBIR
Phase I grant from the National
Science Foundation, along with
private investment from Ladd Energy.
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Applying techniques from modern finance to renewable energy.
Dixon Ladd is conducting research on the application of modern portfolio theory to
assist utilities in optimizing their portfolios of renewable energy products, focusing on
the coincidence of production and demand. Funding is provided by the National
Science Foundation's small business grant program (STTR Phase I).
Title: Timing Is Everything: Matching Wind Production and Electricity Demand Using
Portfolio Theory
Purpose: Dixon Ladd, a subsidiary of Ladd Energy, is developing an algorithm to
compare diurnal and seasonal patterns of electricity production at wind sites with
different profiles of electricity demand by regional utilities. By employing statistical
techniques from the field of security analysis (i.e. stock trading), this tool helps reduce
the impact of wind’s intermittency through diversification of sites.
Abstract: Wind is unpredictably intermittent. By geographically diversifying its portfolio
of wind suppliers, a power purchaser can maximize the correlation of wind energy to its
own diurnal (daily) and seasonal (monthly) demand patterns while reducing the
variance (“firming”) of its wind power supply. Similarly, by conducting this analysis, wind
developers identify those utilities with coincidental demand curves to whom the wind
power will be most valuable. It also helps developers pre-package multiple sites to
increase their value.
This algorithm is being inserted into a web-based tool to perform these analyses,
comparisons, and recommendations in less than 10 seconds with no knowledge of
statistics necessary.
Because wind developers are notoriously secretive about releasing anemometer data,
LE mines public wind data from the U.S. National Climate Data Center and demand
data from the North American Electric Reliability Corporation. Users can upload their
own data while maintaining its confidentiality.
This topic is also important to transmission operators and policy-makers in order to
determine which areas of the nation have wind patterns that best match regional
demand, and thus where transmission construction should occur to optimize utilization
of wind energy. It may also be valuable to forecasters and dispatchers in order to
quickly define geographic areas for further, more detailed study.
This project is funded by the National Science Foundation in collaboration with the
Department of Finance at the University of Wyoming.
Dixon Ladd is conducting research on the application of modern portfolio theory to
assist utilities in optimizing their portfolios of renewable energy products, focusing on
the coincidence of production and demand. Funding is provided by the National
Science Foundation's small business grant program (STTR Phase I).
Title: Timing Is Everything: Matching Wind Production and Electricity Demand Using
Portfolio Theory
Purpose: Dixon Ladd, a subsidiary of Ladd Energy, is developing an algorithm to
compare diurnal and seasonal patterns of electricity production at wind sites with
different profiles of electricity demand by regional utilities. By employing statistical
techniques from the field of security analysis (i.e. stock trading), this tool helps reduce
the impact of wind’s intermittency through diversification of sites.
Abstract: Wind is unpredictably intermittent. By geographically diversifying its portfolio
of wind suppliers, a power purchaser can maximize the correlation of wind energy to its
own diurnal (daily) and seasonal (monthly) demand patterns while reducing the
variance (“firming”) of its wind power supply. Similarly, by conducting this analysis, wind
developers identify those utilities with coincidental demand curves to whom the wind
power will be most valuable. It also helps developers pre-package multiple sites to
increase their value.
This algorithm is being inserted into a web-based tool to perform these analyses,
comparisons, and recommendations in less than 10 seconds with no knowledge of
statistics necessary.
Because wind developers are notoriously secretive about releasing anemometer data,
LE mines public wind data from the U.S. National Climate Data Center and demand
data from the North American Electric Reliability Corporation. Users can upload their
own data while maintaining its confidentiality.
This topic is also important to transmission operators and policy-makers in order to
determine which areas of the nation have wind patterns that best match regional
demand, and thus where transmission construction should occur to optimize utilization
of wind energy. It may also be valuable to forecasters and dispatchers in order to
quickly define geographic areas for further, more detailed study.
This project is funded by the National Science Foundation in collaboration with the
Department of Finance at the University of Wyoming.