Document Open Access Logo

Polyhedral Risk Measures and Lagrangian Relaxation in Electricity Portfolio Optimization

Authors Andreas Eichhorn, Werner Römisch, Isabel Wegner



PDF
Thumbnail PDF

File

DagSemProc.05031.23.pdf
  • Filesize: 162 kB
  • 3 pages

Document Identifiers

Author Details

Andreas Eichhorn
Werner Römisch
Isabel Wegner

Cite AsGet BibTex

Andreas Eichhorn, Werner Römisch, and Isabel Wegner. Polyhedral Risk Measures and Lagrangian Relaxation in Electricity Portfolio Optimization. In Algorithms for Optimization with Incomplete Information. Dagstuhl Seminar Proceedings, Volume 5031, pp. 1-3, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2005)
https://doi.org/10.4230/DagSemProc.05031.23

Abstract

We present a multistage stochastic programming model for mean-risk optimization of electricity portfolios containing physical components and energy derivative products. Stochasticity enters the model via the uncertain (time-dependent) prices and electricity demand. The objective is to maximize the expected overall revenue and, simultaneously, to minimize a multiperiod risk measure, i.e., a risk measure that takes into account the intermediate time cash values. We compare the effect of different multiperiod risk measures taken from the class of polyhedral risk measures which was suggested in our earlier work. Furthermore, we discuss how such a mean-risk optimization problem can be solved by dual decomposition techniques (Lagrangian relaxation).
Keywords
  • Stochastic Programming
  • Mean-Risk Optimization
  • Risk Measure
  • Lagrangian Relaxation
  • Electricity;

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail