| edoc-Server der Humboldt-Universität zu Berlin |
| Autor(en): | Nicole Gröwe-Kuska; Werner Römisch | Titel: | Stochastic unit commitment in hydro-thermal power production planning |
| Erscheinungsjahr: | 2002 |
| Erschienen in: |
Preprints aus dem Institut für Mathematik 3 (Mathematik-Preprints) ISSN: 0863-0976 |
| Volltext: | pdf (urn:nbn:de:kobv:11-10052502) |
| Fachgebiet(e): | Mathematik |
| Schlagwörter (eng): | Lagrangian relaxation, Stochastic programming, bundle methods, unit commitment, scenario tree generation |
| Herausgeber: | Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, Institut für Mathematik |
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| Abstract (eng): | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| We present a mixed-integer multistage stochastic programming model for the short term unit commitment of a hydro-thermal power system under uncertainty in load, inflow to reservoirs, and prices for fuel and delivery contracts. The model is implemented for uncertain load and tested on realistic data from a German power utility. Load scenario trees are generated by a procedure consisting of two steps: (i) Simulation of load scenarios using an explicit respresentation of the load distribution and (ii) construction of a tree out of these scenarios. The dimension of the corresponding mixed-integer programs ranges up to 200,000 binary and 350,000 continuous variables. The model is solved by a Lagrangian-based decomposition strategy exploiting the loose coupling structure. Solving the Lagrangian dual by a proximal bundle method leads to a successive decomposition into single unit subproblems, which are solved by specific algorithms. Finally, Lagrangian heuristics are used to construct nearly optimal first stage decisions. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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