基于压缩感知与ISTA的宽频振荡扰动源分级定位方法

Hierarchical Localization Method of Broadband Oscillation Disturbance Source Based on Compressive Sensing and ISTA

“双高”电力系统发展趋势下宽频振荡问题日益凸显,电力电子设备与电网相互作用呈强时变性与非线性,导致准确的振荡扰动源定位难以实现。为此,提出基于压缩感知与软阈值迭代算法(iterative shrinkage-thresholding algorithm,ISTA)的广域系统振荡扰动源分级定位方法。首先,采取Shapelet算法构建以时序信号为输入的定位启动判据,并生成测量矩阵同步压缩振荡信号。然后,主站根据判据结果,基于振荡压缩信号定位扰动区域。最后,利用ISTA网络复原原始振荡信号,实现振荡源精确定位。应用所提方法于含风电场的四机两区域系统扰动源定位任务,结果证明此方法可突破奈奎斯特采样定理限制,且在低计算需求状况下实现高准确度扰动源定位。

Under the development trend of high proportion of renewable energy and power electronic equipment,the problem of broadband oscillation is becoming more and more prominent.The interaction between power electronic equipment and power grid is strongly time-varying and nonlinear,which makes it difficult to accurately locate the source of oscillation disturbance.This paper proposes a hierarchical localization method of oscillatory disturbance sources in wide-area systems based on compressed sensing and iterative shrinkage-thresholding algorithm(ISTA).Firstly,the Shapelet algorithm is used to construct the positioning initiation criterion with the timing signal as the input,and the measurement-matrix synchronous-compression oscillation signal is generated.Then,the master station locates the dis-turbance area based on the oscillation compression signal according to the result of the criterion.Finally,the ISTA network is used to restore the original oscillatory signal to achieve precise positioning of the oscillatory source.The pro-posed method is applied for the location task of disturbance source of a four-machine two-area system with wind farms.The results show that the proposed method can break through the limitation of the Nyquist sampling theorem and achieve high-accuracy disturbance source location under the condition of low computational requirements.