Lihua Yu, University of Arizona
Talat Genc, University of Arizona
(SPEPS)
INFORMS (Linthicum, Md.)
To export the complete metadata set as Endote or Bibtex format please click to the appropriate link.
| edoc-Server der Humboldt-Universität zu Berlin |
| Author(s): |
Suvrajeet Sen, University of Arizona Lihua Yu, University of Arizona Talat Genc, University of Arizona | Title: | A stochastic programming approach to power portfolio optimization |
| Date of Acceptance: | 09.01.2003 |
| Submission Date: | 14.12.2002 |
| Series Title: |
Stochastic Programming E-Print Series (SPEPS) |
| Editors: | Julie L. Higle; Werner Römisch; Surrajeet Sen |
| Submitted in: |
Operations research INFORMS (Linthicum, Md.) |
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Endnote Bibtex |
| Abstract (eng): | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| The DASH model for Power Portfolio Optimization provides a tool which helps decision-makers coordinate production decisions with opportunities in the wholesale power market. The methodology is based on a stochastic programming model which selects portfolio positions that perform well on a variety of scenarios generated through statistical modeling and optimization. When compared with a commonly used fixed-mix policy, our experiments demonstrate that the DASH model provides significant advantages over several fixed-mix policies. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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