Stochastic Optimization of Electricity Portfolios: Scenario Tree Modeling and Risk Management

We present recent developments in the field of stochastic programming with regard to application in power management. In particular, we discuss issues of scenario tree modeling, that is, appropriate discrete approximations of the underlying stochastic parameters. Moreover, we suggest risk avoidance strategies via the incorporation of so-called polyhedral risk functionals into stochastic programs. This approach, motivated through tractability of the resulting problems, is a constructive framework providing particular flexibility with respect to the dynamic aspects of risk.

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