摘要
进行电能质量扰动分析、扰动治理设备参数调整以及经济调度控制策略制定需要的准确实时可靠的数据信息,将基于全极点模型的线性预测优化算法(LPC)成功引入到电能质量扰动中。线性预测的电能扰动检测系统,其可以通过对样本数据信息自动学习获得误差最小的线性预测模型,以实现对电能质量扰动的在线分析检测。通过试验仿真分析表明,应用线性预测模型对电能质量扰动信号的检测和扰动起始时间、持续时间以及扰动工况点特性数据的提取是可行和有效的,该装置有很好的实用价值和应用前景。
In order to carry out the analysis of power quality disturbance, adjust the disturbance control equipment parameters and formulate the economic dispatching control strategy, a reasonable and precise data should be obtained, based on a novel method based on all pole model - Linear Predictive Coding （LPC） model. With the LPC error minimization self learning model method the power quality disturbance signal can be detected and analyzed online. The result shows the availabil-ity and effectiveness of the proposed LPC method on detecting the power quality disturbance signal and analyzing the start time, duration and the conditions characteristic data, this device has good practical value and application prospect.
出处
《电力电容器与无功补偿》
2013年第6期80-83,共4页
Power Capacitor & Reactive Power Compensation
关键词
电网
电能质量
扰动信号
线性预测
检测
power grid
power quality
disturbance signal
linear prediction
detection
