首页> 外文OA文献 >Real-time power system disturbance identification and its mitigation using an enhanced least squares algorithm
【2h】

Real-time power system disturbance identification and its mitigation using an enhanced least squares algorithm

机译:使用增强最小二乘算法的实时电力系统扰动识别及其缓解

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

This thesis proposes, analyses and implements a fast and accurate real-time power system disturbances identification method based on an enhanced linear least squares algorithm for mitigation and monitoring of various power quality problems such as current harmonics, grid unbalances and voltage dips. The enhanced algorithm imposes less real-time computational burden on processing the system and is thus called “efficient least squares algorithm”. The proposed efficient least squares algorithm does not require matrix inversion operation and contains only real numbers. The number of required real-time matrix multiplications is also reduced in the proposed method by pre-performing some of the matrix multiplications to form a constant matrix. The proposed efficient least squares algorithm extracts instantaneous sine and cosine terms of the fundamental and harmonic components by simply multiplying a set of sampled input data by the pre-calculated constant matrix. A power signal processing system based on the proposed efficient least squares algorithm is presented in this thesis. This power signal processing system derives various power system quantities that are used for real-time monitoring and disturbance mitigation. These power system quantities include constituent components, symmetrical components and various power measurements. The properties of the proposed power signal processing system was studied using modelling and practical implementation in a digital signal processor. These studies demonstrated that the proposed method is capable of extracting time varying power system quantities quickly and accurately. The dynamic response time of the proposed method was less than half that of a fundamental cycle. Moreover, the proposed method showed less sensitivity to noise pollution and small variations in fundamental frequency. The performance of the proposed power signal processing system was compared to that of the popular DFT/FFT methods using computer simulations. The simulation results confirmed the superior performance of the proposed method under both transient and steady-state conditions. In order to investigate the practicability of the method, the proposed power signal processing system was applied to two real-life disturbance mitigation applications namely, an active power filter (APF) and a distribution synchronous static compensator (D-STATCOM). The validity and performance of the proposed signal processing system in both disturbance mitigations applications were investigated by simulation and experimental studies.The extensive modelling and experimental studies confirmed that the proposed signal processing system can be used for practical real-time applications which require fast disturbance identification such as mitigation control and power quality monitoring of power systems.
机译:本文提出,分析和实现了一种基于增强线性最小二乘算法的快速,准确的实时电力系统扰动识别方法,用于缓解和监测各种电能质量问题,例如电流谐波,电网不平衡和电压骤降。增强算法对系统的处理施加了较少的实时计算负担,因此被称为“高效最小二乘算法”。所提出的有效最小二乘算法不需要矩阵求逆运算,而仅包含实数。通过预先执行一些矩阵乘法以形成恒定矩阵,在提出的方法中还减少了所需的实时矩阵乘法的数量。所提出的高效最小二乘法通过简单地将一组采样输入数据与预先计算的常数矩阵相乘来提取基波分量和谐波分量的瞬时正弦和余弦项。本文提出了一种基于提出的高效最小二乘算法的电力信号处理系统。该功率信号处理系统可导出用于实时监视和缓解干扰的各种功率系统量。这些电力系统数量包括组成部分,对称部分和各种功率测量。使用建模和在数字信号处理器中的实际实现,研究了所提出的功率信号处理系统的特性。这些研究表明,提出的方法能够快速,准确地提取随时间变化的电力系统数量。该方法的动态响应时间少于基本周期的一半。此外,所提出的方法显示出对噪声污染的敏感性较低,并且基频变化较小。拟议的功率信号处理系统的性能与使用计算机模拟的流行DFT / FFT方法的性能进行了比较。仿真结果证实了该方法在瞬态和稳态条件下均具有优越的性能。为了研究该方法的实用性,将所提出的功率信号处理系统应用于两个现实生活中的缓解干扰应用,即有源功率滤波器(APF)和配电同步静态补偿器(D-STATCOM)。通过仿真和实验研究了所提出的信号处理系统在减扰应用中的有效性和性能。广泛的建模和实验研究证实,所提出的信号处理系统可用于需要快速识别干扰的实际实时应用。例如电力系统的缓解控制和电能质量监控。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号