DocumentCode
2673779
Title
Algorithms for mean-risk stochastic integer programs in energy
Author
Schultz, Rüdiger ; Neise, Frederike
Author_Institution
Dept. of Mathematics, Duisburg Univ.
fYear
0
fDate
0-0 0
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
Keywords
cogeneration; distributed power generation; integer programming; linear programming; risk analysis; stochastic programming; dispersed generation; mean-risk stochastic integer programs; mixed-integer linear programming solver; risk aversion; stochastic programming problems; Distributed power generation; Energy storage; Mathematical model; Mathematical programming; Mathematics; Power generation; Power system modeling; Random variables; Stochastic processes; Uncertainty; Cogeneration; Decomposition methods; Dispersed storage and generation; Mathematical Programming; Renewable Resources; Risk aversion; Uncertanity;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location
Montreal, Que.
Print_ISBN
1-4244-0493-2
Type
conf
DOI
10.1109/PES.2006.1708985
Filename
1708985
Link To Document