Multi-stage fully adaptive distributionally robust unit commitment for power system based on mixed approximation rules

被引:0
|
作者
Liu, Mao [1 ]
Kong, Xiangyu [1 ]
Ma, Chao [1 ]
Zhou, Xuesong [2 ]
Lin, Qingxiang [1 ]
机构
[1] Tianjin Univ, Key Lab Smart Grid, Minist Educ, Tianjin 300072, Peoples R China
[2] Tianjin Univ Technol, Sch Elect Engn & Automat, Tianjin 300384, Peoples R China
基金
中国国家自然科学基金;
关键词
Multi-stage Distributionally robust unit; commitment; Mixed approximation rule; Data-driven; Dual theory; Sequential decision-making; OPTIMIZATION; DISPATCH; MODEL;
D O I
10.1016/j.apenergy.2024.124051
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The escalating integration of renewable energy sources necessitates enhanced power system flexibility. Gas units, with their rapid start-stop capabilities, emerge as crucial assets for system operators grappling with supplydemand fluctuations. This paper proposes a novel multi-stage fully adaptive distributionally robust unit commitment (MFA-DRUC) model to optimize the operation of these flexible units under the uncertainties inherent in real-time dispatch. Leveraging the Wasserstein metric, our approach significantly expands the feasible solution space compared to traditional multi-stage adaptive unit commitment (MA-DRUC) models, bolstering resilience against extreme scenarios. To overcome the computational challenges posed by the model's multi-stage structure, we introduce a mixed approximation rule (MAR) that effectively handles high-dimensional variables and strong coupling characteristics. By employing duality theory, we transform the unit commitment (UC) problem into a computationally tractable mixed-integer linear programming problem. Comprehensive simulations across power systems of varying scales, encompassing scenarios such as coal-fired unit decommissioning and gas unit integration, validate the efficacy of our proposed MFA-DRUC model. These results underscore its potential to enhance the reliability and efficiency of power systems navigating the complexities of a renewables-driven future.
引用
收藏
页数:15
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