Title :
Algorithms for mean-risk stochastic integer programs in energy
Author :
Schultz, Rüdiger ; Neise, Frederike
Author_Institution :
Dept. of Mathematics, Duisburg Univ.
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;
Conference_Titel :
Power Engineering Society General Meeting, 2006. IEEE
Conference_Location :
Montreal, Que.
Print_ISBN :
1-4244-0493-2
DOI :
10.1109/PES.2006.1708985
