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Novel measurement based load modeling and demand side control methods for fault induced delayed voltage recovery mitigation.

机译:基于新的基于测量的负载建模和需求侧控制方法,用于缓解故障引起的延迟电压恢复。

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摘要

The continuous increase in electric energy demand and limitations in the reinforcement of generation and transmission systems, have progressively led to a greater utilization of power systems and transmission lines. As a result, system conditions may arise where voltage collapse phenomena have a high probability to occur, either due to the accidents in the system structure, or to load becoming particularly heavy. Recently, "Workshop on Residential Air Conditioner (A/C) Stalling" of Department of Energy (DOE) reported that fault-induced delayed voltage recovery (FIDVR) is now a national issue since residential A/C penetration across U.S. is at an all time high and growing rapidly. The unique characteristics of air conditioner load could cause short-term voltage instability, fast voltage collapse, and delayed voltage recovery. In order to study and mitigate FIDVR problem, a systematic load modeling methodology utilizing novel parameter identification technique and an online demand side control scheme based on load shedding strategy are developed in this dissertation.;As load characteristics change from traditional incandescent light bulbs to power electronics-based loads, and as the characteristics of motors change with the emergence of high-efficiency, low-inertia motor loads, it is critical to understand and model load responses to ensure stable operations of the power system during different contingencies. Developing "better" load models, therefore, has been an important issue for power system analysis and control. It is necessary to take advantage of the state-of-the-art techniques for load modeling and develop a systematic approach to establish accurate, aggregate load models for bulk power system stability studies. In this dissertation, a systematic methodology is provided to derive aggregate load models at the high voltage level (transmission system level) using measurement-based approach. A novel parameter identification technique via hybrid learning is also developed for deriving load model parameters accurately and efficiently.;According to NERC's definition, FIDVR is defined as the phenomenon whereby system voltage remains at significantly reduced levels for several seconds after a fault in transmission, subtransmission, or distribution has been cleared. Various studies have shown that FIDVR usually occurs in the areas dominated by induction motors with constant torque. These motors can stall in response to sustained low voltage and draw excessive reactive power from the power grid. Since no under voltage or stall protection is equipped with A/Cs, they can only be tripped by thermal protection which takes 3 to 20 seconds. Severe FIDVR event could lead to fast voltage collapse. In this dissertation, a novel online demand side control method utilizing motor kinetic energy is developed for disconnecting stalling motors at the transmission level to mitigate FIDVR and fast voltage collapse.
机译:电能需求的不断增加以及发电和输电系统的加强受到限制,逐渐导致了电力系统和输电线路的更大利用。结果,可能由于系统结构中的事故或负载变得特别重的情况而出现电压崩溃现象的可能性很高的系统状况。最近,美国能源部(DOE)的“家用空调(A / C)失速车间”报告说,由于在美国的住宅A / C普及率非常高,故障引起的延迟电压恢复(FIDVR)现在已成为一个国家问题。时间高,增长迅速。空调负载的独特特性可能导致短期电压不稳定,快速电压崩溃和延迟电压恢复。为了研究和缓解FIDVR问题,本文研究了一种新颖的参数辨识技术和基于减载策略的在线需求侧控制方案的系统负荷建模方法。负载,并且随着电动机特性的变化,伴随着高效,低惯量的电动机负载的出现,了解和建模负载响应以确保电力系统在不同情况下稳定运行至关重要。因此,开发“更好的”负载模型一直是电力系统分析和控制的重要问题。有必要利用最新技术进行负荷建模,并开发一种系统的方法来建立准确的总负荷模型,以进行大功率电力系统的稳定性研究。本文提供了一种系统的方法,以基于测量的方法来推导高电压水平(输电系统水平)的总负荷模型。还开发了一种通过混合学习的新型参数识别技术,可准确高效地导出负载模型参数。根据NERC的定义,FIDVR被定义为一种现象,在传输,子传输故障后,系统电压会在几秒钟内保持显着降低的水平,或分配已被清除。各种研究表明,FIDVR通常发生在以恒定转矩感应电机为主的区域。这些电动机可能会响应持续的低压而失速,并从电网汲取过多的无功功率。由于没有配备任何欠压或失速保护的A / C,它们只能通过需要3到20秒的热保护来跳闸。严重的FIDVR事件可能导致快速电压崩溃。本文研究了一种利用电动机动能的在线需求侧控制方法,用于在传动级断开失速电动机的连接,以减轻FIDVR和快速电压崩溃的风险。

著录项

  • 作者

    Bai, Hua.;

  • 作者单位

    Iowa State University.;

  • 授予单位 Iowa State University.;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 161 p.
  • 总页数 161
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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