ALGORITHMS FOR MEAN-RISK STOCHASTIC INTEGER PROGRAMS IN ENERGY

Authors

  • Rüdiger Schultz Department of Mathematics University of Duisburg-Essen, Campus Duisburg Lotharstr. 65, D-47048 Duisburg
  • Frederike Neise Department of Mathematics University of Duisburg-Essen, Campus Duisburg Lotharstr. 65, D-47048 Duisburg

Keywords:

Dispersed storage and generation, Cogeneration, Renewable Resources, Mathematical Programming, Uncertainty, Decomposition methods, Risk aversion

Abstract

We introduce models and algorithms suitable for including risk aversion into stochastic programming problems in
energy. For a system with dispersed generation of power and heat we present computational results showing the
superiority of our decomposition algorithm over a standard mixed-integer linear programming solver

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Published

2023-06-29

How to Cite

Schultz, R., & Neise, F. (2023). ALGORITHMS FOR MEAN-RISK STOCHASTIC INTEGER PROGRAMS IN ENERGY. Investigación Operacional, 28(1). Retrieved from https://revistas.uh.cu/invoperacional/article/view/6373

Issue

Vol. 28 No. 1 (2007): Investigacion Operacional

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.