Optimal Power Flow Models With Probabilistic Guarantees: A Boolean Approach
Optimal Power Flow Models With Probabilistic Guarantees: A Boolean Approach
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DOI：
10.1109/tpwrs.2020.3016178
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发表时间：
2020-08
影响因子：
6.6
通讯作者：
M. Lejeune;P. Dehghanian
中科院分区：
文献类型：
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作者：
M. Lejeune;P. Dehghanian
由于缺乏对主要不确定性的认识，以及可再生能源产量的突然变化，可再生能源高度扩散的电网中传统的最优潮流（OPF）调度可能面临风险。这可能反过来导致传输线功率流明显超过的情况，随后发生自动保护动作。针对OPF问题，提出了一种新的广义联合机会约束模型，该模型能有效地捕捉系统中可再生能源发电的随机性。针对所提出的具有概率保证的优化模型的复杂性和非凸性，我们提出了一种新的易处理的布尔方法，将该模型转化为等效的确定性混合整数线性问题，该问题可以通过现成的求解器快速有效地求解。数值结果验证了该模型和布尔方法的有效性。
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.