Distributionally Robust Unit Commitment with N-k Security Criterion and Operational Flexibility of CSP

被引:0
作者
Pei, Younan [1 ]
Han, Xueshan [1 ]
Ye, Pingfeng [2 ]
Zhang, Yumin [1 ]
Li, Mingbing [3 ]
Mao, Huizong [3 ]
机构
[1] Shandong Univ, Key Lab Power Syst Intelligent Scheduling & Contro, Minist Educ, Jinan 250061, Peoples R China
[2] Shandong Univ Sci & Technol, Coll Energy Storage Technol, Qingdao 266590, Peoples R China
[3] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
基金
中国国家自然科学基金;
关键词
ambiguity sets; distribution uncertainty; imprecise Dirichlet model; N-k security criterion; solar-thermal power generation; REAL-TIME DISPATCH; DISTRIBUTION-SYSTEMS; ECONOMIC-DISPATCH; RISK-ASSESSMENT; WIND FARM; OPTIMIZATION; MODEL;
D O I
10.3390/en15239202
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
In order to reduce the conservatism of the robust optimization method and the complexity of the stochastic optimization method and to enhance the ability of power systems to deal with occasional line fault disturbance, this paper proposes a distributionally robust unit commitment (DRUC) model with concentrating solar power (CSP) operational flexibility and N-k safety criterion under distributed uncertainty. According to the limited historical sample data, under the condition of satisfying a certain confidence level, based on the imprecise Dirichlet model (IDM), an ambiguity set is constructed to describe the uncertainty of transmission line fault probability. Through the identification of the worst probability distribution in the ambiguity set, the adaptive robust optimal scheduling problem is transformed into a two-stage robust optimization decision model under the condition of deterministic probability distribution. The CSP flexibility column and constraint generation (C&CG) algorithm is used to process the model and the main problem and subproblem are solved by using the Big-M method, linearization technique, and duality principle. Then, a mixed integer linear programming problem (MILP) model is obtained, which effectively reduces the difficulty of solving the model. Finally, case studies on the IEEE 14 bus system and the IEEE 118 bus system demonstrate the efficiency of the proposed method, such as enhancing the ability of power systems to cope with occasional line fault disturbances and reducing the conservatism of the robust optimization method.
引用
收藏
页数:21
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