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Uncertainty Tracing of Distributed Generations via Complex Affine Arithmetic Based Unbalanced Three-Phase Power Flow

机译:基于复杂仿射算法的不平衡三相潮流对分布式发电的不确定性跟踪

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Variations of load demands and generations bring multiple uncertainties to power system operation. Under this situation, power flows become increasingly uncertain, especially when significant distributed generations (DGs), such as wind and solar, are integrated into power systems. In this paper, a Complex Affine arithmetic based unbalanced Three-phase Forward-Backward Sweep power flow model (CATFBS) is proposed to study the impacts of uncertainties in unbalanced three-phase distribution systems. An index of Relative Influence of Uncertain Variables on Outcomes (RIUVO) is proposed for quantifying the impacts of individual uncertain factors on power flows and bus voltages. The CATFBS method is tested on the modified IEEE 13-bus system and a modified 292-bus system. Numerical results show that the proposed method outperforms the Monte Carlo method for exploring the impacts of uncertainties on the operation of distribution systems. The proposed CATFBS method can be used by power system operators and planners to effectively monitor and control unbalanced distribution systems under various uncertainties.
机译:负载需求和发电量的变化给电力系统的运行带来了多种不确定性。在这种情况下,电力流变得越来越不确定,尤其是当风能和太阳能等重要的分布式发电(DG)集成到电力系统中时。本文提出了一种基于复杂仿射算法的不平衡三相正反扫频潮流模型(CATFBS),以研究不确定性对三相不平衡配电系统的影响。提出了不确定变量对结果的相对影响(RIUVO)的指数,用于量化各个不确定因素对潮流和母线电压的影响。 CATFBS方法在改进的IEEE 13总线系统和改进的292总线系统上进行了测试。数值结果表明,所提出的方法优于蒙特卡洛方法,用于探索不确定性对配电系统运行的影响。电力系统运营商和计划人员可以使用所提出的CATFBS方法来有效地监视和控制在各种不确定性下的不平衡配电系统。

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