首页> 外文期刊>Energy Reports >The 6th International Conference on Power and Energy Systems Engineering (CPESE 2019), September 20–23, 2019, Okinawa, Japan A dynamic partitioning method for power system parallel restoration considering restoration-related uncertainties
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The 6th International Conference on Power and Energy Systems Engineering (CPESE 2019), September 20–23, 2019, Okinawa, Japan A dynamic partitioning method for power system parallel restoration considering restoration-related uncertainties

机译:第六次国际电力和能源系统会议(CPESE 2019),2019年9月20日至23日,日本冲绳,考虑恢复相关的不确定因素的电力系统并行恢复的动态分区方法

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摘要

Online Decision Support System (DSS) for restorative control can be used to track the restoration process of power system dynamically and optimize the restoration plans online to support the decision-making of dispatchers’ online restorative control. Parallel restoration can improve the restoration efficiency effectively, but the division of the restoration partitions should match the real-time conditions of the power grid. This paper proposes a dynamic partitioning method for power system restoration considering the restoration capabilities of partitions, which can be used to refresh the partitioning results dynamically based on the power system restoration process so as to cope with the restoration-related uncertainties. Furthermore, the restoration targets (outage power plants and outage substations) of partitions will be filtered and evaluated based on its restoration values to maximize the overall restoration revenues. A decision support system for restorative control is developed and a case study using data of a real regional grid in China is conducted to illustrate the flexibility and effectiveness of the proposed method in dealing with restoration-related uncertainties.
机译:用于修复控制的在线决策支持系统(DSS)可用于动态跟踪电力系统的恢复过程,并优化在线恢复计划,以支持调度员在线修复控制的决策。并行恢复可以有效地提高恢复效率,但恢复分区的划分应匹配电网的实时条件。本文提出了一种动态分配方法,用于考虑分区的恢复能力,可以使用基于电力系统恢复过程动态地刷新分区结果,以便应对与恢复相关的不确定性。此外,将基于其恢复值来筛选和评估分区的恢复目标(中断电厂和中断变电站,以最大限度地提高整体恢复收入。开发了一种恢复控制的决策支持系统,并进行了使用中国真实区域网格数据的案例研究,以说明所提出的方法在处理相关的不确定性方面的灵活性和有效性。

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