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An islanding partition method of active distribution networks based on chance-constrained programming

机译:基于机会约束规划的主动分配网络岛屿分区方法

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With the high integration of uncontrollable distributed generators (NDGs) comprising photovoltaic arrays (PVs) and wind turbines (WTs), many technical issues have become increasingly prominent in the islanding operation of active distribution networks (ADNs). Such problems including branch overloading and voltage violations threaten the secure operation of distribution systems and a continuous power supply. To address the uncertainties of NDG outputs when implementing islanding partition strategies, this paper proposes a new method of the islanding partition of ADNs based on chance-constrained programming. First, power generation scenarios and probability distributions for these scenarios are generated according to historical data considering the time series characteristics and uncertainties of NDGs. Then, the chance-constrained description of islanding operation is expanded to consider the effect of uncertainties related to NDGs. Moreover, an islanding partition model of ADNs based on chance-constrained programming is established. By applying convex relaxation and introducing auxiliary variables, the model is converted to a mixed-integer quadratically constrained programming model that can be effectively solved. Finally, case studies involving the modified IEEE 33-node system, IEEE 123-node system and an actual distribution system are conducted to verify the effectiveness and scalability of the proposed method.
机译:利用包括光伏阵列(PVS)和风力涡轮机(WTS)的无法控制的分布式发电机(NDGS)的高集成,在主动分配网络(ADN)的岛屿运行中,许多技术问题已经越来越突出。包括分支过载和电压违规的这些问题威胁到分配系统和连续电源的安全操作。为了解决诸如实施岛屿分区策略时纳尔格产出的不确定性,本文提出了一种基于机会约束规划的ADNS岛屿分区的新方法。首先,考虑到NDGS的时间序列特征和不确定性,根据历史数据生成这些情况的发电场景和概率分布。然后,扩展了孤岛操作的机会约束描述,以考虑与NDGS相关的不确定性的影响。此外,建立了基于机会约束编程的ADN的岛屿分区模型。通过应用凸松弛和引入辅助变量,该模型被转换为可以有效解决的混合整数二次约束编程模型。最后,进行涉及修改的IEEE33节点系统,IEEE 123节点系统和实际分配系统的案例研究以验证所提出的方法的有效性和可扩展性。

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