Optimal Power Flow Models With Probabilistic Guarantees: A Boolean Approach

被引:9
|
作者
Lejeune, Miguel A. [1 ,2 ]
Dehghanian, Payman [2 ]
机构
[1] George Washington Univ, Dept Decis Sci, Washington, DC 20052 USA
[2] George Washington Univ, Dept Elect & Comp Engn, Washington, DC 20052 USA
基金
美国国家科学基金会;
关键词
Uncertainty; Probabilistic logic; Power transmission lines; Reliability; Stochastic processes; Wind power generation; Transmission line matrix methods; Boolean; joint chance constraints; optimal power flow (OPF); stochastic programming; uncertainty;
D O I
10.1109/TPWRS.2020.3016178
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The legacy Optimal Power Flow (OPF) dispatch in electric power grids with high proliferation of renewables can be at risk due to the lack of awareness on major uncertainties, and sudden changes in renewable outputs. This may, in turn, result in conditions where transmission line power flows are significantly exceeded, and subsequent automatic protective actions take place. This letter presents a new generalized joint chance-constrained model for the OPF problem that effectively captures the stochasticity in renewable power generation in the system. In dealing with the complexity, and non-convexity of the proposed optimization model with probabilistic guarantees, we propose a novel tractable Boolean method to transform the model into an equivalent deterministic mixed-integer linear problem, which can be solved quickly, and efficiently by off-the-shelf solvers. Numerical results verify the effectiveness of the proposed model, and the suggested Boolean methodology.
引用
收藏
页码:4932 / 4935
页数:4
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