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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Osorio, G.J. Lujano-Rojas, J.M. Matias, J.C.O. Catalao, J.P.S. |
| Copyright Year | 2015 |
| Description | Author affiliation: Univ. Beira Interior, Covilha, Portugal (Osorio, G.J.; Lujano-Rojas, J.M.; Matias, J.C.O.; Catalao, J.P.S.) |
| Abstract | Due to increasing integration of renewable generation into the electrical framework in last decades, the mathematical techniques required for the optimal day-ahead scheduling needs to be continuously improved, specifically for modeling the variability of these sources. In this paper, a method for producing a new solution for the stochastic unit commitment (UC) problem from the analysis of each scenario is developed. The methodology described in this paper can deal with a large number of scenario sets with a reasonable computational effort, by finding the common and feasible solutions for the scenario set under analysis. |
| Starting Page | 533 |
| Ending Page | 537 |
| File Size | 313834 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781467372039 |
| ISSN | 21555532 |
| e-ISBN | 9781479999781 |
| DOI | 10.1109/PowerEng.2015.7266372 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-11 |
| Publisher Place | Latvia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Stochastic unit commitment Priority list Uncertainty Stochastic processes Wind power generation Generators Power systems Wind power forecasting error Forecasting Scenario sets Optimization |
| Content Type | Text |
| Resource Type | Article |
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