Approximate dynamic programming for storage problems
Storage problems are an important subclass of stochastic control problems. This paper presents a new method, approximate dynamic programming for storage, to solve storage problems with continuous, convex decision sets. Unlike other solution procedures, ADPS allows math programming to be used to make decisions each time period, even in the presence of large state variables. We test ADPS on the day ahead wind commitment problem with storage. Copyright 2011 by the author(s)/owner(s).
Proceedings of the 28th International Conference on Machine Learning, Icml 2011
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