智能配电网复杂电气信号特性表征及参量估计方法研究

With the development of distributed generation and the change of load characteristics, the electrical signals of distribution grids display growing prominence of time-variability, uncertainty and frequency spectrum complexity. Consequently, the existing methods on electrical parameter estimation are facing serious challenges in high accuracy, real-time response and signal feature extraction capability..The characterization of electrical signals and estimation of electrical parameters are the basic issues on monitoring, control and protection in smart distribution grid (SDG). This proposal aims at exploring the time-frequency domain characteristics of SDG electrical signals under complex electrical environment and establishing mathematical models of electrical signals for electrical parameter estimation. The estimation algorithms of SDG electrical parameter under steady-, dynamic- and transient-state is going to be studied, the internal connection and exchange mechanism in the stable and transient state algorithms are going to be revealed, and an unified digital filter architecture for these algorithms is going to be designed. So that the steady-state measurement precision, dynamic tracking speed of electrical signals and the performance of related intelligent electronic devices can be improved. In addition, the measurement methods of electrical signal complexity and similarity, together with the extraction method of waveform shape feature, are going to be investigated. New electrical parameters with profound physical meaning and high application value are going to be refined and defined. Therefore, the modes of characterizing the electrical signals can be expanded, and the efficacy of extracting signal characteristics can be improved. By the research proposed in this proposal, not only the analysis theory of electrical signals will be developed, but efficient and reliable information support for SDG monitoring, control and protection will be provided.

随着分布式发电的发展和负荷特性的变化，配电网电气信号呈现日益显著的时变性、不确定性和频谱复杂性，现有电参量估计方法的精确性、实时性及信号特征提取能力面临挑战。.电气信号特性表征及参量估计是智能配电网测量、控制和保护的基础科学问题。 本项目拟探究智能配电网复杂电气环境下电气信号的时频域特性，建立面向电参量估计的电气信号数学观测模型； 研究配电网稳态、机电暂态、电磁暂态下基本电参量的数字估计算法，揭示稳态和暂态算法的内在联系及转换机制，提出算法的数字滤波器统一实现架构，以提高电气信号的稳态测量精度和动态跟踪速度，改善智能测控设备性能； 研究电气信号复杂性、相似性的测度方法及波形形状特征的提取方法，凝练和定义具有物理意义和应用价值的新型电参量，以拓展电气信号特性的表征方式，提升特征信息提取效能。 发展电气信号分析理论与电参量估计方法，为配电网智能控制与保护提供高效可靠的信息技术支撑。

配电网电气环境日益复杂，电气信号在更多场合表现出愈来愈显著的多样性、时变性、不确定性和频谱复杂性，现有电气信号分析方法在信号特性表征和参量估计方面不能满足智能配电网的许多工程应用需求。项目主要从以下2个方面展开研究：（1）研究智能配电网电气信号特性表征方法。针对已有电参量不能有效表征复杂信号特性、难以精细提取配电网异常或故障信号信息的问题，提炼了表征信号波形形状、相似度、复杂度等特性的具有物理意义和应用价值的新型电参量；提出了基于动态时间弯曲距离的电气信号相似性测度方法，并应用于有源配电网馈线保护和小电流接地故障定位，解决了馈线终端采样信号时间同步精度不高时和数据丢失时信号相似性准确度量的问题，确保了馈线保护的可靠性和故障定位的正确性；提出了基于峭度、偏度的电气信号波形特性表征方法，有效提取正常信号、特殊/异常信号和故障信号的波形特性差异，并应用于小电流接地故障检测和变压器励磁涌流识别等工程难题，可精确捕捉故障发生时刻，可靠地检测三相不平衡、间歇性电弧接地、高阻接地、低信噪比等情况下的单相接地故障，提升变压器励磁涌流识别的正确率。（2）研究配电网不同运行状态下电气信号基本电参量的估计算法。针对含谐波、衰减直流分量及强噪声、强扰动、强时变等因素下电参量难以快速准确估计的问题，建立了配电网复杂电气信号的统一状态空间模型，提出了基于强跟踪泰勒-卡尔曼滤波器的动态相量实时估计算法，通过信号模型中考虑因素的合理取舍，并采用级联延时信号消除滤波等技术，可满足配电网在稳态、机电暂态和故障情况下电参量估计在精度和实时性方面的不同要求，提高电气信号的稳态测量精度和动态跟踪速度；提出了配电线路合闸涌流波形特征提取及工频电参量计算方法，实现了配电线路合闸涌流自适应闭锁。上述研究发展和丰富了电气信号分析理论与电参量估计方法，为配电网测量与保护提供了新的信号处理手段。

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