分布式光伏发电并网系统孤岛检测技术研究

发布时间：2018-06-19 10:19

本文选题：光伏并网发电系统 + 孤岛检测　；参考：《新疆大学》2017年硕士论文

【摘要】：能源攸关民生国计。为了解决日益凸显的能源问题,人们把目光投向了以光伏、风力发电为代表的新能源。其中光伏发电得到最广泛的应用。随着光伏发电系统数量的增多,会给原配电网的安全及稳定性带来一系列的危害,这其中主要的影响就是孤岛效应。为了最大可能的减小孤岛效应的危害,研究性能良好的孤岛检测方法有着重要的现实作用。本文阐述了检测孤岛效应的背景,并对孤岛效应的定义以及带来的危害作了介绍,叙述了目前关于孤岛检测方法的研究现状。探讨了孤岛产生的机理,介绍了国际经常使用的检测孤岛效应的方法以及评价该方法优劣的标准。对每种孤岛检测法的检测原理及存在的优缺点进行分析总结。以主动式检测法中的主动移相法为研究对象,阐述了该方法的检测原理。首先在Matlab/Simulink上进行建模与仿真,并以检测速度和存在的检测盲区两方面作为指标来对其检测性能进行评价。其次以自动移相法为基础,分析该类方法检测时间长的原因,并提出一种改进的自动移相法,并通过仿真验证了该方法可以提高检测效率,减小盲区。为了克服传统被动式孤岛检测方法检测盲区较大的问题,在不影响电能质量的情况下,研究了基于小波包能量熵和BP神经网络的被动式孤岛检测方法。在此方法中,对公共耦合点的电压信号和逆变器输出电流信号进行小波包分解,得到相应的小波包能量熵作为特征量,由BP神经网络对特征量进行识别获取分类结果,从而实现孤岛检测。仿真结果表明了基于小波包能量熵与BP神经网络的孤岛检测方法能够迅速地检测出孤岛,而且对电能质量无影响。
[Abstract]:Energy is of vital importance to the nation. In order to solve the increasingly prominent energy problems, people focus on photovoltaic, wind power as the representative of new energy. Photovoltaic power generation is the most widely used. With the increase of the number of photovoltaic power generation system, it will bring a series of harm to the safety and stability of the original distribution network, the main impact of which is the islanding effect. In order to reduce the harm of islanding effect as far as possible, it is very important to study the method of islanding detection with good performance. In this paper, the background of detecting islanding effect is described, the definition and harm of islanding effect are introduced, and the present research status of islanding detection method is described. The mechanism of islanding is discussed. The method of detecting islanding effect and the standard of evaluating the method are introduced. The detection principle and advantages and disadvantages of each islanding detection method are analyzed and summarized. Taking the active phase shift method as the research object, the principle of the active phase shift method is expounded. Firstly, modeling and simulation are carried out on Matlab / Simulink, and the detection performance is evaluated by using the detection speed and the existing blind spot as indicators. Secondly, based on the automatic phase shift method, the reason of the long detection time is analyzed, and an improved automatic phase shift method is proposed. The simulation results show that the method can improve the detection efficiency and reduce the blind area. In order to overcome the problem of large blind spot detection in traditional passive islanding detection, a passive islanding detection method based on wavelet packet energy entropy and BP neural network is studied without affecting the power quality. In this method, the common coupling point voltage signal and inverter output current signal are decomposed by wavelet packet, the corresponding wavelet packet energy entropy is obtained as the characteristic quantity, and the classification result is obtained by BP neural network. Thus the detection of isolated islands is realized. The simulation results show that the islanding detection method based on wavelet packet energy entropy and BP neural network can detect the isolated island quickly and has no effect on the power quality.
【学位授予单位】：新疆大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM615

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