2021•2021 Power System and Green Energy Conference (PSGEC)Requires access
Power System State Estimation Based on PMU Under Linear Bayesian Theory
Wenchao Song, Chao Lü, Junjie Lin, Chengzhi Zhu, Shujun Zhang
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Abstract
With the rapid changes in the actual power system operation mode, power system wide area real time state estimation based on phasor measurement unit (PMU) plays an increasingly important role in energy management system (EMS). However, complex distribution characteristics of PMU measurement error pose challenges to the accuracy of state estimation. Therefore, a state estimation method combining PMU linear measurement model and linear Bayesian estimation is proposed. Considering the prior information of estimated parameters and the complex probability density function of measurement error, linear Bayesian estimation is applied to power system state estimation based on PMU. The correlation between real measurement error and imaginary measurement error is analyzed, and the prior information of estimated parameters is obtained according to the analysis of system state volatility. Compared with complex number least squares (CLS) method, the applicability and accuracy of this method were verified in IEEE 39 bus system.