摘要
现代电力系统的电网结构和负荷构成出现了新的变化趋势,随之带来的电能质量问题逐渐引起电力部门和用户的高度重视。电能质量监测是监督、改善电能质量的前提条件,对保证电力系统的安全经济运行与用户用电安全具有重要的理论与实际意义。现代电力系统运行与智能电网发展对电能质量监测技术提出了更高的要求。局限于稳态电能质量检测的传统仪器仪表已不再满足需要,暂态电能质量检测越来越成为关注的焦点,更多、更直观的关于电能质量的实时信息成为必须。而如何对海量测量数据进行有效地存储与传输成为电能质量监测技术发展过程中亟待解决的问题。本文针对目前电能质量监测技术中存在的问题展开了研究工作。
论文首先研究了稳态电能质量检测方法,通过测试各项稳态电能质量指标验证了方法的准确性。利用数学形态学实时性强的优点并根据各种暂态扰动波形的特征,提出了一种基于数学形态学的暂态电能质量检测方法,通过对常见暂态电能质量扰动信号进行定位与分类验证了方法的可行性。电能质量检测结果作为录波启动判据与电能质量监测系统的分析依据。
针对电能质量录波数据的存储与传输问题,本文借鉴图像压缩方法,提出了一种基于提升格式的2维离散小波变换、SPIHT编码与算术编码的数据压缩方法。通过对常见电能质量扰动数据进行压缩,证明了该方法具有良好的压缩性能且可通过控制压缩码率控制压缩比,有利于根据网络状况调节传输的数据量。
基于电能质量检测方法与录波数据压缩方法,本文设计了电能质量综合检测与数据管理系统,并详细阐述了系统设计与实现的过程。该系统以LabVIEW为开发平台,实现了稳态与暂态电能质量的综合检测、录波数据压缩、网络化、数据库访问等功能,以形象、直观的形式显示检测与分析结果,满足现代电能质量监测技术要求,具有较好的理论与实际意义。
There are new trends in the grid and load structure of modern power system, leading to various power quality problems which have aroused great attention of power departments and users. Power quality monitoring is a prerequisite for supervising and improving power quality, and a guarantee for power system’s safe and economic operation and users’security. Thus, it’s significant in both theory and practice. The operation of modern power system and the development of smart grid put forward higher requirement for power quality monitoring technology. Traditional instruments limited to steady-state power quality detection no longer meet the requirements, since dynamic quality detection becomes more and more concerned and more intuitive real-time information about power quality is necessary. How to solve the problem of saving and transmitting vast amounts of measurement data is urgent in the development process of power quality monitoring technology. To address problems existing in present power quality monitoring technology, researches are conducted in this paper.
Steady-state power quality detection algorithms are discussed in this paper, the accuracy of which is verified by measuring various power quality indices. Taking advantage of good real-time performance of mathematical morphology and according to waveform characteristics of various transient disturbances, an algorithm based on mathematical morphology is presented in this paper, the feasibility of which is verified by detecting usual dynamic quality disturbances. Power quality detection results function as data recording criterion and analysis basis in power quality monitoring system.
To handle the problem of storing and transmitting a large number of measurement data, a data compression method based on two-dimension discrete wavelet transform (2-D DWT) in lifting format, set partitioning in hierarchical tree (SPIHT) coding with arithmetical coding is presented in this paper. The high compression performance of which is verified by compressing several kinds of frequent power quality disturbance data. And the compression ratio can be regulated by changing the bit-rate, thus the amount of data can be adjusted to the network environment.
Based on the above power quality detection algorithms and data compression method, the power quality integrated detection and data management system is designed in this paper, and the design and implementation process are presented in detail. With LabVIEW as a development platform, the system has achieved functions of integrated detection of steady-state and dynamic quality, recorded data compression, network, database access and etc, and provided image and intuitive detection and analysis results. It’s significant both in theory and practice respects.
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