基于状态空间转换的SCADA系统支路静态参数局部辨识方法

Local Area Identification of Static Branch Parameters Based on State Space Transformation in SCADA System

电网支路静态参数中存在的偏差或误差会严重影响电网状态估计及后续高级应用的有效性。以电网支路静态参数为状态量,根据SCADA量测系统的特点,提出了针对电网支路静态不良参数的局部估计辨识算法。利用拉格朗日乘子法得到的参数检测结果,以可疑支路为中心,向外搜索形成局部估计区域,按照量测类型以支路参数为状态变量建立量测方程,再将局部区域内的可信任支路参数作为伪量测加入量测方程,提高量测冗余度。在局部区域内对可疑支路参数进行估计辨识,经多断面的统计分析给出可疑支路参数的建议修正值。考虑到SCADA系统中无法直接应用电压量测值,构造了关于支路参数的不动点迭代格式,利用内外两层迭代来实现对支路参数的估计辨识。最后在IEEE118节点系统上验证了算法的有效性,并讨论了量测误差对辨识结果的影响。

The deviation or error in the static parameters of power network branches will seriously affect effectiveness of power network state estimation and subsequent advanced applications.This paper proposes a local estimation and identification algorithm based on the characteristics of SCADA measurement system.Lagrange multiplier method is used to get the test results of parameters,the suspicious branch is taken as the center and the local estimation region is searched outward.Then,according to measurement type,a measurement equation is established with the parameters as a state vector.Finally,the trusted branch parameters in the local area are added into the measurement equation as pseudo-measurements to improve measurement redundancy.The suspected branch parameters are identified in the local area,and the results are given through multi-section statistical analysis.Considering that the voltage amplitude measurements in SCADA system cannot be directly used,a fixed-point iteration scheme for branch parameters is constructed,and estimation of branch parameters is processed with two nested loop iterations.Effectiveness of the algorithm is verified on IEEE 118-bus system,and the influence of measurement errors on identification results is also discussed.