Highly-efficient single-level robust transmission expansion planning approach applicable to large-scale renewable energy integration

被引:1
作者
Zeng, X. [1 ]
Chen, J. [1 ]
Yin, X. [1 ,2 ]
Chen, H. [1 ]
Liang, Z. [3 ]
Zhang, S. [1 ]
Tan, B. [4 ]
机构
[1] South China Univ Technol, Sch Elect Power, Wushan Rd 381, Guangzhou 510640, Peoples R China
[2] Univ New South Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
[3] Hong Kong Polytech Univ, Dept Elect & Elect Engn, Hong Kong, Peoples R China
[4] Wuyi Univ, Sch Mech & Automat Engn, Yingbin Rd 99, Jiangmen 529020, Peoples R China
关键词
Uncertainty; Transmission expansion planning; Probability identification; Robustness; Optimality; Single-level mixed-integer linear programming;
D O I
10.1016/j.segan.2024.101486
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
Robust transmission expansion planning (RTEP) approaches are crucial for addressing the uncertainty associated with renewable energy sources (RESs). However, existing methods often yield overly conservative solutions and exhibit low computational efficiency, especially when dealing with a large number of RES units. To overcome these limitations, we propose a simplified single-level RTEP framework based on scenarios captured in advance from historical data by searching the vertices of a convex hull. These scenarios, referred to as robust scenarios, are guaranteed to produce robust solutions that are consistent with the traditional two-stage adaptive robust TEP (ARTEP) approach in terms of robustness and optimality. Finally, the speed for solving the single-level model is increased by applying a probability-based method to determine the odds of the robust scenarios being the worstcase scenario. Numerical results obtained for the Garver 6-bus system, the IEEE 118-bus system, and the Polish 2383-bus system demonstrate that the proposed approach saves 91.71 %, 93.39%, and 98.84% of the required computational time, respectively, compared to the ARTEP approach.
引用
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页数:13
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