Keywords
uncertainty of wind power, ambiguity set, unit commitment, distributionally robust chance constraint, unimodality
Abstract
The continuous improvement of wind power penetration has greatly reduced the consumption of fossil fuels and greenhouse gas emissions. However, the uncertainty and intermittent nature of wind power make the solution to the traditional unit commitment infeasible. In order to describe the uncertainty of wind power generation, this paper introduces an ellipsoid ambiguty set based on moment information, and applies the chance constraint to the unit combination model to change the power balance constraint into a soft constraint. Then, the distributionally robust optimization method is utilized, and the unit commitment model is reformulated into a mixed integer linear programming problem by linearization method. In addition, two improved methods, the limiting the distribution of ambiguty set with unimodality and adjusting confidence level according to time, are proposed to improve the economics of the model. Finally, case analysis and numerical results verify the practicality and feasibility of the proposed model and method.
DOI
10.19781/j.issn.1673-9140.2021.02.006
First Page
51
Last Page
57
Recommended Citation
Liu, Ming; Zeng, Chengbi; and Miao, Hong
(2021)
"Distributionally robust chance-constrained unit commitment model considering uncertainty of wind power,"
Journal of Electric Power Science and Technology: Vol. 36:
Iss.
2, Article 6.
DOI: 10.19781/j.issn.1673-9140.2021.02.006
Available at:
https://jepst.researchcommons.org/journal/vol36/iss2/6