Research on perception of power system state based on WAMS

The development of Smart Grid requires more accurate and fast for perception, assessment and control of power system state. Widely installed phasor measurement units (PMU) and mass PMU measurements provide a good foundation for this requirement, because PMU can directly measure bus voltage phasors at the rate of tens of milliseconds. Thus, the number of PMU installed in the power grid and the reliability and accuracy of PMU measurements are of great importance, which directly affect the feasibility and reliability of state perception. Actually, PMU measurements may contain bad data and the accuracy of phase measurements is not high enough. Estimation method is an effective way to deal with data contaminated by noise and bias. In this paper, we proposes the complex number weighted least squares (CWLS) estimation algorithm to process PMU measurements directly in the complex domain to obtain more accurate system state. Phasor error characteristics in the complex domain are analyzed depth which shows the proposed algorithm is robust to phase error. Meanwhile, an effective bad data identification method is proposed. Test results demonstrate the performance of the CWLS algorithm from the perspectives of computional efficiency, estimation quality and adaptability to inconsistent measurment errors, the robustness of the CWLS algorithm and the effectiveness of the proposed bad data identification method is also shown in the tests.