Distributionally robust optimization scheduling of a joint wind-solar-storage system considering step-type carbon trading

被引：0
|
作者：
Zhao Y. [1 ]
Wang W. [1 ]
Yan S. [1 ]
机构：
[1] Xinjiang University, Engineering Research Center, Education Ministry for Renewable Energy Power Generation and Grid Connection, Urumqi
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2023年 / 51卷 / 06期
基金：
中国国家自然科学基金;
关键词：
carbon trading; distributionally robust optimization; optimal dispatch; uncertainty; Wasserstein distance; wind-solar-storage system;
D O I：
10.19783/j.cnki.pspc.220771
中图分类号：
学科分类号：
摘要：
Under the "dual carbon" target, the penetration of wind, solar and other clean energy will continue to increase, producing a scheduling problem brought by the uncertainty of its power generation. Thus a two-stage distributionally robust optimization model for the wind-solar-storage system is proposed. To reduce the carbon emissions of the system, step-type carbon trading is introduced. In the model, the operating cost of the system is minimized according to the forecast information in the first stage. In the second stage, Wasserstein distance is used to construct a fuzzy set of data-driven output errors. An affine strategy is used to adjust the model so that the system can meet the worst condition in the fuzzy set and the adjustment cost is minimized. Finally, a strong duality principle is used to transform the two-stage distributionally robust optimization model into the equivalent MILP model. Through the analysis of numerical examples, it is compared and verified that the use of traditional units can be significantly reduced by considering the step-type carbon trading through reasonable scheduling, and the applicability and superiority of distributionally robust optimization model is demonstrated. © 2023 Power System Protection and Control Press. All rights reserved.
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页码：127 / 136
页数：9
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