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Time and order recursive estimation of power system electromechanical modes using synchro-phasors.

机译:使用同步相量的电力系统机电模式的时间和顺序递归估计。

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摘要

The electrical power system is a critical infrastructure. Power system blackouts have deep social and economic ill-impacts. Deregulation of the electricity market, decrease in the rate of development of new energy infrastructure, higher penetration of non-committable renewable generators and ever increasing energy demand have forced the system operators to work the system close its stability limits and therefore closer to such eventualities. Consequently, it has become imperative that the stability of the system be determined in real-time.;The steady state stability of the system is often described in terms of the frequency and damping of the electromechanical modes of the system. Recent advances in synchrophasor technology have allowed researchers and operators to supplement the traditional model driven calculations of the modes with measurement based estimation techniques. These estimates are sensitive to user choices such as the number of parameters to be used.;This dissertation presents a real-time algorithm with a modular structure for the estimation of the modes using ambient measurements from the grid. The modularity of the method alleviates the requirement of fixing the number of parameters by providing simultaneous estimates for all choices of the length of the prediction filter. Furthermore, a real-time algorithm may be troubled by bad data. To that end, the dissertation modifies the said algorithm to cope with such situations.;The confidence in mode estimates is expressed as an estimate of standard deviation for both the frequency and damping estimates. Two methods are presented -- an analytical method and a quasi-numerical method. This dissertation also examines recursive whiteness testing of the prediction residuals as a means of model validation. The whiteness testing is useful in suggesting a reasonable model order.;Robustness, order recursiveness and real-time qualities of the algorithm, together with methods for estimating standard deviations in the mode estimates and recursive whiteness testing, provide a good alternative to the traditional estimation techniques. The applicability of these methods is verified using simulated and measured synchro-phasor data from the western North American power system.
机译:电力系统是关键的基础设施。电力系统停电会对社会和经济造成深远的影响。电力市场的放松管制,新能源基础设施发展速度的降低,不可承诺的可再生发电机的普及率不断提高以及能源需求的不断增加,迫使系统运营商在接近其稳定性极限的情况下努力使系统工作,因此更容易发生这种情况。因此,迫切需要实时确定系统的稳定性。经常根据系统的机电模式的频率和阻尼来描述系统的稳态稳定性。同步相量技术的最新进展已使研究人员和操作人员可以使用基于测量的估计技术来补充模式的传统模型驱动计算。这些估计值对用户选择(例如要使用的参数数量)敏感。本论文提出了一种实时的算法,该算法具有模块化结构,可以使用来自网格的环境测量值来估计模式。该方法的模块化通过为预测滤波器的长度的所有选择提供同时的估计,减轻了固定参数数量的需求。此外,实时算法可能会受到不良数据的困扰。为此,本文修改了所述算法以应对这种情况。模式估计的置信度表示为频率和阻尼估计的标准偏差的估计。提出了两种方法-分析方法和准数值方法。本文还研究了预测残差的递归白度测试作为模型验证的一种方法。白度测试对于建议合理的模型阶数很有用。算法的鲁棒性,阶数递归性和实时质量,以及在模式估计和递归白度测试中估计标准偏差的方法,为传统估计提供了很好的选择技术。这些方法的适用性已使用来自北美西部电力系统的仿真和测量的同步相量数据进行了验证。

著录项

  • 作者

    Pai, Gurudatha K.;

  • 作者单位

    University of Wyoming.;

  • 授予单位 University of Wyoming.;
  • 学科 Statistics.;Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 178 p.
  • 总页数 178
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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