Optimal Power Generation under Uncertainty via Stochastic Programming (1997)
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| Venue: | in: Stochastic Programming Methods and Technical Applications (K. Marti and P. Kall Eds.), Lecture Notes in Economics and Mathematical Systems |
| Citations: | 19 - 8 self |
BibTeX
@INPROCEEDINGS{Dentcheva97optimalpower,
author = {Darinka Dentcheva and Werner Römisch},
title = {Optimal Power Generation under Uncertainty via Stochastic Programming},
booktitle = {in: Stochastic Programming Methods and Technical Applications (K. Marti and P. Kall Eds.), Lecture Notes in Economics and Mathematical Systems},
year = {1997},
pages = {22--56},
publisher = {Springer-Verlag}
}
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Abstract
: A power generation system comprising thermal and pumpedstorage hydro plants is considered. Two kinds of models for the cost-optimal generation of electric power under uncertain load are introduced: (i) a dynamic model for the short-term operation and (ii) a power production planning model. In both cases, the presence of stochastic data in the optimization model leads to multi-stage and two-stage stochastic programs, respectively. Both stochastic programming problems involve a large number of mixedinteger (stochastic) decisions, but their constraints are loosely coupled across operating power units. This is used to design Lagrangian relaxation methods for both models, which lead to a decomposition into stochastic single unit subproblems. For the dynamic model a Lagrangian decomposition based algorithm is described in more detail. Special emphasis is put on a discussion of the duality gap, the efficient solution of the multi-stage single unit subproblems and on solving the dual problem...







