In robust optimization problems, building a proper uncertainty set for the stochastic variables plays an important role. Due to the restricted mathematical formulations of the uncertainty sets, the results derived from conventional two-stage robust optimization are usually over conservative. In this paper, a novel data-adaptive robust optimization method for the unit commitment is proposed for the power system with wind farms integrated. The extreme scenario extraction and the two stage robust optimization are combined in the proposed method. The data-adaptive set consisting of a few extreme scenarios is derived to reduce the conservativeness by considering the temporal and spatial correlations of multiple wind farms. Numerical results demonstrate that the proposed data-adaptive robust optimization algorithm is less conservative than the current two-stage optimization approaches while maintains the same level of robustness of the solution.
|Conference||IEEE Power and Energy Society General Meeting (PESGM)|
|Period||05/08/2018 → 09/08/2018|
|Series||IEEE Power and Energy Society General Meeting|
- Unit commitment
- Two-stage robust optimization
- Temporal and spatial correlations
- Data-adaptive uncertainty set