Risk Modeling via Stochastic Dominance in Power Systems with Dispersed Generation

We propose a new approach to risk modeling in power optimization employing the concept of stochastic domi- nance. This leads to new classes of large-scale block-structured mixed-integer linear programs for which we present decompo- sition algorithms. The new methodology is applied to stochastic optimization problems related to operation and investment plan- ning in a power system with dispersed generation. Index Terms— Dispersed storage and generation, Cogenera- tion, Renewable resources, Mathematical optimization, Uncer- tainty and risk modeling, Stochastic dominance, Decomposition methods