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Optimal Power Flow Models With Probabilistic Guarantees: A Boolean Approach

机译:具有概率保证的最佳功率流模型:布尔方法

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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.
机译:由于对重大不确定性缺乏意识,并且可再生产出的突然变化,具有高增殖可再生能源的电力电网(OPF)派遣的遗产率可能存在风险。反过来,这可能导致传输线功率流动显着超过的条件,并且发生后续的自动保护动作。这封信为OPF问题提供了一种新的广义联合机会约束模型,有效地捕获了系统中可再生能源发电的瞬极性。在处理具有概率保证的提议优化模型的复杂性和非凸性时,我们提出了一种新颖的贸易布尔方法,将模型转换为等效的确定性混合整数线性问题,这可以快速,有效地解决 - 搁板的求解器。数值结果验证了所提出的模型的有效性,以及建议的布尔方法。

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