逆变式DG并网孤岛检测研究
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摘要
本文以逆变式DG并网系统为载体研究一种新的孤岛检测方法。论文首先对并网系统的各部分组成结构进行详细分析和设计,在暂态仿真软件PSCAD/EMTDC环境下搭建并网模型。仿真并网系统正常、孤岛、短路等11种运行状态,采集各状态下并网点的三相电流信号,并在Matlab中实现特征提取。最后结合AINMC分类算法进行孤岛状态判别。本文研究的是一种被动式孤岛检测方法,对电网电能质量无影响,检测准确率高,检测盲区小,具有一定的实际应用参考价值。
论文主要包括以下几个部分：
1、介绍DG系统并网方式及标准,分析DG并网对配电网的影响,阐述孤岛检测的意义及国内外研究现状。
2、研究孤岛检测的机理、检测标准及盲区等基本问题,分析国内外现有孤岛检测方法的原理、优缺点及应用场合。其中,实际应用较多的被动式检测方法不影响电网电能质量,但检测盲区较大。针对此问题,本文探索一种新的被动式检测方法。
3、设计并网系统仿真模型,包括逆变器拓扑结构分析、LCL滤波器设计以及逆变器控制模型研究。首先,通过逆变器拓扑结构分析确定本系统并网逆变器为三相电压型逆变结构；然后,设计LCL并网滤波器参数,并仿真验证滤波器具有良好性能；最后,研究并网逆变器控制模型。本系统采用双环控制,设计电压环和电流环PI调节器,仿真分析逆变器并网控制方法和参数设计的效果。
4、第4、5章介绍新的被动式孤岛检测方法。第4章利用小波包奇异熵(WPSE)提取并网系统PCC点电流信号特征值,作为孤岛检测的特征量。特征量分析实验表明,各运行状态特征量分离度较大,能有效地分离出孤岛信号。
5、最后一章将所提取的特征量输入到人工免疫网络分类器中实现孤岛检测。此过程采用改进的AINMC算法对特征量进行分类器训练,然后利用KNN算法实现孤岛判别。在Matlab中编程实现整个分类过程。程序运行结果表明,待分类参量(未知运行状态下的特征量数据)输入后,输出类别基本符合预期结果,分类效果较好。说明本文所研究的孤岛检测方法效果明显。
The islanding detection method studied in this paper is based on grid-connected of inverter-based DG Firstly, it needs to analysis and design every part of the grid system and build the grid-connected model in the transient simulation software PSCAD/EMTDC. The simulation simulates eleven kinds of operating status, such as normal, islanding and a variety of short circuits. Collect the three-phase current signals of each state and extract the feature in Matlab. Finally, the feature vector will be analyzed AINMC algorithmic to realize the islanding detection. The method studies in the paper are a passive islanding method which does not affect the power quality. It has a high accuracy, a small non-detection zone (NDZ) and a certain reference value of practical application.
The paper includes the following sections:
The opening chapter gives an introduction of the grid-connected mode and standard, analyze its impact on distribution network. Study the meaning and research status at home and abroad of the islanding detection.
In the second part, the paper studies the mechanism, the standard and the non-detection zone of islanding detection. Analyze the methods, principle, advantages, disadvantages and application occasions of the existing detection. The passive detection method has no effect on power quality, but it has a large NDZ. To solve this problem, the paper explores a new passive detection method.
The designed grid-connected model mainly includes three parts:inverter topology, LCL filter and the control method of the inverter. On the basis of studying the inverter topology, select three-phase voltage source inverter as the grid-connected inverter structure. Then analysis and calculation the LCL filter parameter and verify that the design of the filter has a good performance. At last, study the control mode of the grid-connected inverter, the system uses double-loop control. Design the voltage and current loop PI regulator and simulation its functions.
In the forth and fifth chapter, a new islanding detection method is studied. In chapter4, the wavelet packet singular entropy was applied to extract the eigenvalues of three-phase current signals retrieved at PCC point and take it as the feature vector. The experiments show that the feature vector of every state is separate and can help effectively distinguish island status.
In chapter5, the features are put into artificial immune network classifiers to realize island detection. In this process, the improved AINMC algorithm was utilized to train the feature and the KNN algorithm to classify. The whole process is implemented by programming in Matlab. The result shows that the output categories of the classifiers in line with expected result when the classified parameters (the feature vector of unknown running state) are put into the classifier. The islanding detection method studied in this paper has a good effection.
论文主要包括以下几个部分：
1、介绍DG系统并网方式及标准,分析DG并网对配电网的影响,阐述孤岛检测的意义及国内外研究现状。
2、研究孤岛检测的机理、检测标准及盲区等基本问题,分析国内外现有孤岛检测方法的原理、优缺点及应用场合。其中,实际应用较多的被动式检测方法不影响电网电能质量,但检测盲区较大。针对此问题,本文探索一种新的被动式检测方法。
3、设计并网系统仿真模型,包括逆变器拓扑结构分析、LCL滤波器设计以及逆变器控制模型研究。首先,通过逆变器拓扑结构分析确定本系统并网逆变器为三相电压型逆变结构；然后,设计LCL并网滤波器参数,并仿真验证滤波器具有良好性能；最后,研究并网逆变器控制模型。本系统采用双环控制,设计电压环和电流环PI调节器,仿真分析逆变器并网控制方法和参数设计的效果。
4、第4、5章介绍新的被动式孤岛检测方法。第4章利用小波包奇异熵(WPSE)提取并网系统PCC点电流信号特征值,作为孤岛检测的特征量。特征量分析实验表明,各运行状态特征量分离度较大,能有效地分离出孤岛信号。
5、最后一章将所提取的特征量输入到人工免疫网络分类器中实现孤岛检测。此过程采用改进的AINMC算法对特征量进行分类器训练,然后利用KNN算法实现孤岛判别。在Matlab中编程实现整个分类过程。程序运行结果表明,待分类参量(未知运行状态下的特征量数据)输入后,输出类别基本符合预期结果,分类效果较好。说明本文所研究的孤岛检测方法效果明显。
The islanding detection method studied in this paper is based on grid-connected of inverter-based DG Firstly, it needs to analysis and design every part of the grid system and build the grid-connected model in the transient simulation software PSCAD/EMTDC. The simulation simulates eleven kinds of operating status, such as normal, islanding and a variety of short circuits. Collect the three-phase current signals of each state and extract the feature in Matlab. Finally, the feature vector will be analyzed AINMC algorithmic to realize the islanding detection. The method studies in the paper are a passive islanding method which does not affect the power quality. It has a high accuracy, a small non-detection zone (NDZ) and a certain reference value of practical application.
The paper includes the following sections:
The opening chapter gives an introduction of the grid-connected mode and standard, analyze its impact on distribution network. Study the meaning and research status at home and abroad of the islanding detection.
In the second part, the paper studies the mechanism, the standard and the non-detection zone of islanding detection. Analyze the methods, principle, advantages, disadvantages and application occasions of the existing detection. The passive detection method has no effect on power quality, but it has a large NDZ. To solve this problem, the paper explores a new passive detection method.
The designed grid-connected model mainly includes three parts:inverter topology, LCL filter and the control method of the inverter. On the basis of studying the inverter topology, select three-phase voltage source inverter as the grid-connected inverter structure. Then analysis and calculation the LCL filter parameter and verify that the design of the filter has a good performance. At last, study the control mode of the grid-connected inverter, the system uses double-loop control. Design the voltage and current loop PI regulator and simulation its functions.
In the forth and fifth chapter, a new islanding detection method is studied. In chapter4, the wavelet packet singular entropy was applied to extract the eigenvalues of three-phase current signals retrieved at PCC point and take it as the feature vector. The experiments show that the feature vector of every state is separate and can help effectively distinguish island status.
In chapter5, the features are put into artificial immune network classifiers to realize island detection. In this process, the improved AINMC algorithm was utilized to train the feature and the KNN algorithm to classify. The whole process is implemented by programming in Matlab. The result shows that the output categories of the classifiers in line with expected result when the classified parameters (the feature vector of unknown running state) are put into the classifier. The islanding detection method studied in this paper has a good effection.
引文
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