基于广域测量系统及Prony算法的低频振荡分析
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摘要
随着电网互联的加快、电力市场的引入、单台机组发电容量的增大、大容量能源输送形式的形成,电力系统的稳定性问题日益突出,低频振荡是现代电力系统稳定问题的主要表现形式。本文基于广域测量系统应用改进Prony算法对电力系统低频振荡进行分析和研究。
分析了广域测量系统的组成、特点,探讨了其在电力系统中的应用,利用其实时同步的特点对电力系统的动态信息进行采集,应用广域测量信号分析电力系统低频振荡。
研究了Prony算法,用两种判据确定影响算法准确性的样本函数矩阵阶数、并对算法参数的计算进行简化；利用多信号分析对Prony算法进行改进,提出同类信号、非同类信号的分类多信号分析方法,以提高算法的准确性。
在多信号改进Prony算法分析的基础上,进一步对其在大系统下的应用进行了扩展。利用Prony算法的模式参数定义了系统的模式能量参与度,在小干扰稳定分析中参与因子矩阵的基础上,构造出反映系统相关性关系的相关矩阵,以此作为大系统下分类多信号改进Prony算法信号的选取依据,将所提改进算法应用到大系统中。
应用本文研究的改进算法对EPRI-36系统进行低频振荡分析,得到了系统的振荡模式和主导振荡模式,算法分析结果的准确性和有效性得到了改善。
Power system stability in our country is easier to be undermined because of interconnected network speeding up, electric power market introduced, generation unit capacity increased as well as large-capacity energy transmission pattern shaping, and low frequency oscillation which occur frequently is one of the major problems of power system stability. This article presents the analysis of low frequency oscillation in power system in improved Prony algorithm based on wide area measurement system.
WAMS is discussed in the structures, features as well as applications in power system, and wide area measurement signals are prepare for analysis of low frequency oscillation in power system because of WAMS can grasp the dynamic information from signals characterized by synchronization and wide-measurement.
Prony algorithm widely used in power system is researched in both reckon of sample function matrix order in two criterions and algorithm parameters simplified calculation. To improve Prony algorithm, similar, non-similar signals are defined and sorted multi-signals improved Prony algorithm is proposed to analyze low frequency oscillation.
In large-scale system, the paper makes a further effort to improve the Prony algorithm. Model energy correlativity is defined from Prony algorithm parameters and structured into correlation matrix based on correlation factor matrix in small signal stability analysis. The correlation matrix can reflect generation unit correlativity and be as basis of dividing signals in sorted multi-signals improved Prony algorithm.
The proposed improved Prony algorithms were applied in EPRI-36 system to analyze low frequency oscillation, and the accuracy as well as the validity is demonstrated.
分析了广域测量系统的组成、特点,探讨了其在电力系统中的应用,利用其实时同步的特点对电力系统的动态信息进行采集,应用广域测量信号分析电力系统低频振荡。
研究了Prony算法,用两种判据确定影响算法准确性的样本函数矩阵阶数、并对算法参数的计算进行简化；利用多信号分析对Prony算法进行改进,提出同类信号、非同类信号的分类多信号分析方法,以提高算法的准确性。
在多信号改进Prony算法分析的基础上,进一步对其在大系统下的应用进行了扩展。利用Prony算法的模式参数定义了系统的模式能量参与度,在小干扰稳定分析中参与因子矩阵的基础上,构造出反映系统相关性关系的相关矩阵,以此作为大系统下分类多信号改进Prony算法信号的选取依据,将所提改进算法应用到大系统中。
应用本文研究的改进算法对EPRI-36系统进行低频振荡分析,得到了系统的振荡模式和主导振荡模式,算法分析结果的准确性和有效性得到了改善。
Power system stability in our country is easier to be undermined because of interconnected network speeding up, electric power market introduced, generation unit capacity increased as well as large-capacity energy transmission pattern shaping, and low frequency oscillation which occur frequently is one of the major problems of power system stability. This article presents the analysis of low frequency oscillation in power system in improved Prony algorithm based on wide area measurement system.
WAMS is discussed in the structures, features as well as applications in power system, and wide area measurement signals are prepare for analysis of low frequency oscillation in power system because of WAMS can grasp the dynamic information from signals characterized by synchronization and wide-measurement.
Prony algorithm widely used in power system is researched in both reckon of sample function matrix order in two criterions and algorithm parameters simplified calculation. To improve Prony algorithm, similar, non-similar signals are defined and sorted multi-signals improved Prony algorithm is proposed to analyze low frequency oscillation.
In large-scale system, the paper makes a further effort to improve the Prony algorithm. Model energy correlativity is defined from Prony algorithm parameters and structured into correlation matrix based on correlation factor matrix in small signal stability analysis. The correlation matrix can reflect generation unit correlativity and be as basis of dividing signals in sorted multi-signals improved Prony algorithm.
The proposed improved Prony algorithms were applied in EPRI-36 system to analyze low frequency oscillation, and the accuracy as well as the validity is demonstrated.
引文
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