Dynamic partitioning of island smart distribution systems in emergencies

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Zahra Hosseini Najafabadi, Asghar Akbari Foroud
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Abstract

When a severe fault occurs in the distribution network, all or parts of it may be disconnected from the upstream network. Partitioning of these islanded areas is a solution to supplying the affected loads. Due to the variable nature of loads and renewable distributed generation (DG), the static model of partitioning with a fixed nature during island operation cannot be suitable. Therefore, in this article, considering the variable nature of loads and renewable distributed generation, a dynamic model is presented for the island partitioning to restore more valuable loads, which is suitable for quick decision-making in emergencies. Also, a method for deciding on the mode of charging and discharging storage systems in emergencies is proposed. This model considers time limitation, uncontrollable DGs, controllable DGs and their control, controllability, and priority of loads, tie-switches, storage systems, simultaneous faults, different situations of unintentional islanding of the distribution network, position of switches, and variable nature of loads and distributed generations. So, it is more comprehensive than the previous methods. Applying the proposed model to the modified IEEE 69-bus system with controllable and uncontrollable generation and storage systems assuming different scenarios shows the effectiveness of the proposed scheme.

Abstract Image

紧急情况下岛屿智能配电系统的动态分区
当配电网络发生严重故障时,全部或部分配电网络可能会与上游网络断开。对这些孤岛区域进行分区是向受影响负荷供电的一种解决方案。由于负荷和可再生分布式发电(DG)的可变性,孤岛运行期间固定性质的静态分区模型并不适用。因此,考虑到负荷和可再生分布式发电的可变性,本文提出了一种动态模型,用于岛屿分区,以恢复更有价值的负荷,该模型适用于紧急情况下的快速决策。此外,还提出了一种在紧急情况下决定储能系统充放电模式的方法。该模型考虑了时间限制、不可控的 DG、可控的 DG 及其控制、可控性、负载的优先级、连接开关、储能系统、同时发生的故障、配电网意外孤岛的不同情况、开关的位置以及负载和分布式发电的可变性。因此,它比以往的方法更加全面。将提出的模型应用于带有可控和不可控发电和储能系统的改进型 IEEE 69 总线系统,并假设了不同的情况,显示了提出的方案的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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