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Aalborg Universitet Data-adaptive Robust Optimization Method for the Economic Dispatch of Active Distribution Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Hai-Bo |
| Copyright Year | 2018 |
| Abstract | Due to the restricted mathematical description of the uncertainty set, the current two-stage robust optimization is usually over-conservative which has drawn concerns from the power system operators. This paper proposes a novel dataadaptive robust optimization method for the economic dispatch of active distribution network with renewables. The scenariogeneration method and the two-stage robust optimization are combined in the proposed method. To reduce the conservativeness, a few extreme scenarios selected from the historical data are used to replace the conventional uncertainty set. The proposed extremescenario selection algorithm takes advantage of considering the correlations and can be adaptive to different historical data sets. A theoretical proof is given that the constraints will be satisfied under all the possible scenarios if they hold in the selected extreme scenarios, which guarantees the robustness of the decision. Numerical results demonstrate that the proposed data-adaptive robust optimization algorithm with the selected uncertainty set is less conservative but equally as robust as the existing two-stage robust optimization approaches. This leads to the improved economy of the decision with uncompromised security. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://vbn.aau.dk/ws/portalfiles/portal/293128954/Data_adaptive_Robust_Optimization_Method_for_the_Economic_Dispatch_of_Active_Distribution_Networks.pdf |
| Alternate Webpage(s) | http://vbn.aau.dk/files/293128954/Data_adaptive_Robust_Optimization_Method_for_the_Economic_Dispatch_of_Active_Distribution_Networks.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
