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A Distribution Network Reconfiguration and Islanding Strategy

机译:配电网重构和孤岛策略

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摘要

With the development of Smart Grid, the reliability and stability of the power system are significantly improved. However, a large-scale outage still possibly occurs when the power system is exposed to extreme conditions. Power system blackstart, the restoration after a complete or partial outage is a key issue needed to be studied for the safety of power system. Network reconfiguration is one of the most important steps when crews try to rapidly restore the network. Therefore, planning an optimal network reconfiguration scheme with the most efficient restoration target at the primary stage of system restoration is necessary and it also builds the foundation to the following restoration process. Besides, the utilization of distributed generators (DGs) has risen sharply in the power system and it plays a critical role in the future Smart Grid to modernize the power grid. The emerging Smart Grid technology, which enables self-sufficient power systems with DGs, provides further opportunities to enhance self-healing capability. The introduction of DGs makes a quick and efficient restoration of power system possible.;In this thesis, based on the topological characteristics of scale-free networks and the Discrete Particle Swarm Optimization (DPSO) algorithm, a network reconfiguration scheme is proposed. A power system structure can be converted into a system consisting of nodes and edges. Indices that reflect the nodes' and edges' topological characteristics in Graph Theory can be utilized to describe the importance of loads and transmission lines in the power system. Therefore, indices like node importance degree, line betweenness centrality and clustering coefficient are introduced to weigh the importance of loads and transmission lines. Based on these indices, an objective function which aims to restore as many important loads and transmission lines as possible and also subjected to constraints is formulated. The effectiveness of potential reconfiguration scheme is verified by Depth First Search (DFS) algorithm. Finally, DPSO algorithm is employed to obtain the optimal reconfiguration scheme. The comprehensive reconfiguration scheme proposed by my thesis can be the theoretical basis for the power grid dispatchers.;Besides, DGs are introduced in this thesis to enhance the restoration efficiency and success rate at the primary stage of network restoration. Firstly, the selection and classification principle of DGs are introduced in my thesis. In addition, the start sequence principle of DGs is presented as a foundation for the following stability analysis of network restoration with DGs. Then, the objective function subjected to constraints that aims to restore as many important loads as possible is formulated. Based on the restoration objective, islands that include part of important and restorable loads are formed because the DGs' capacity cannot ensure an entire restoration of the outage areas. Finally, DPSO is used to obtain the optimal solution of islanding strategy and the state sequence matrix is utilized to represent the solution space.;It is believed that this work will provide some useful insight into improving the power system resiliency in the face of extreme events such as natural or man-made disasters.
机译:随着智能电网的发展,电力系统的可靠性和稳定性得到了显着提高。但是,当电源系统暴露于极端条件下时,仍然可能发生大规模停电。电力系统的黑启动,完全或部分停电后的恢复是电力系统安全需要研究的关键问题。当工作人员试图快速恢复网络时,网络重新配置是最重要的步骤之一。因此,有必要在系统还原的最初阶段就规划具有最佳还原目标的最佳网络重配置方案,这也为后续还原过程奠定了基础。此外,电力系统中分布式发电机(DG)的利用率急剧上升,并且在未来的智能电网中实现电网现代化起着至关重要的作用。新兴的智能电网技术可通过DG实现自给自足的电力系统,为增强自愈能力提供了更多机会。 DG的引入为电力系统的快速,高效恢复提供了可能。;本文基于无标度网络的拓扑特征和离散粒子群优化(DPSO)算法,提出了一种网络重构方案。电力系统结构可以转换为由节点和边组成的系统。图论中反映节点和边的拓扑特征的指标可用于描述电力系统中负载和传输线的重要性。因此,引入了诸如节点重要度,线间中心度和聚类系数之类的指标来权衡负载和传输线的重要性。基于这些指标,制定了一个目标函数,旨在恢复尽可能多的重要负载和传输线,并同时受到约束。通过深度优先搜索(DFS)算法验证了潜在的重新配置方案的有效性。最后,采用DPSO算法获得最优的重配置方案。本文提出的综合重构方案可以为电网调度员提供理论依据。此外,本文还引入了分布式分布式控制器,以提高电网恢复初期的恢复效率和成功率。首先,介绍了危险物品的选择和分类原则。此外,DGs的启动顺序原理是为后续DGs网络恢复稳定性分析的基础。然后,制定了受约束的目标函数,该约束旨在恢复尽可能多的重要负载。基于恢复目标,形成了包括重要且可恢复的负载的一部分的孤岛,这是因为DG的能力无法确保中断区域的完整恢复。最后,使用DPSO来获得孤岛策略的最优解,并使用状态序列矩阵来表示解空间。相信这项工作将为提高面对极端事件的电力系统弹性提供一些有用的见识。例如自然或人为灾难。

著录项

  • 作者

    Jiang, Zikai.;

  • 作者单位

    The University of Wisconsin - Milwaukee.;

  • 授予单位 The University of Wisconsin - Milwaukee.;
  • 学科 Electrical engineering.
  • 学位 M.S.
  • 年度 2018
  • 页码 93 p.
  • 总页数 93
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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