This report introduces a two-stage stochastic programming model for committing reserves in systems with large amounts of wind power. It describes wind power generation in terms of a representative set of appropriately weighted scenarios, and it presents a dual decomposition algorithm for solving the resulting stochastic program. The paper tests the scenario generation methodology on a model of California consisting of 122 generators, and it shows that the stochastic programming unit commitment policy outperforms common reserve rules.

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Renewable energy