Estimating Dominant Oscillation Characteristics from Measurement Responses in Power Systems Utilizing Optimized Variable Projection
Li Xue, Yu Yang, Jiang Tao, Chen Houhe, Li Guoqing
Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China
Abstract：Estimating the accurate dynamic feature parameters of electromechanical oscillation, which include the dominant modes, mode shapes and participation factors, are very important for analyzing and damping the electromechanical oscillation in the bulk power grids. This paper develops a holistic assessment framework to estimate the dominant modes, mode shapes and participation factors from the synchrophasor measurements by using the optimized variable projection (OVP) in the power system. The synchrophasor measurements gathered from the PMUs is firstly preprocessed by finite difference method (FDM). Then, the preprocessed measurements are used to construct the low-order state matrix which contains the critical dynamic oscillation features of power systems. According to the constructed the low-order state matrix, the variable projection model is formulated, and the modes and mode shapes can be solved by optimized variable projection (OVP). For the estimated modes and mode shapes, cumulative energy weight of modes is developed to separate the dominant modes and their mode shapes of power systems from the estimated results. Further, the participation factors are estimated by using the separated dominant mode shapes. Finally, the proposed method is evaluated by the IEEE 68-bus test system as well as China Southern Power Grid. The results confirm that the proposed OVP based dynamic assessment approach performs great accuracy and effectiveness to estimate dominant modes and mode shapes from the synchrophasor measurements in bulk power grids.
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2022, Vol. 37 
