Large-Scale Stochastic Mixed-Integer Programming Algorithms for Power Generation Scheduling [chapter]

Kibaek Kim, Victor M. Zavala
<span title="">2016</span> <i title="Springer International Publishing"> Alternative Energy Sources and Technologies </i> &nbsp;
This chapter presents a stochastic unit commitment model for power systems and revisits parallel decomposition algorithms for these types of models. The model is a two-stage stochastic programming problem with first-stage binary variables and second-stage mixed-binary variables. The here-and-now decision is to find day-ahead schedules for slow thermal power generators. The wait-and-see decision consists of dispatching power and scheduling fast-start generators. We discuss advantages and
more &raquo; ... ons of different decomposition methods and provide an overview of available software packages. A large-scale numerical example is presented using a modified IEEE 118-bus system with uncertain wind power generation.
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