Conditional Maximum Likelihood of Three-Phase Phasor Estimation for μPMU in Active Distribution Networks

Micro phasor measurement units (mu PMU) installed in active distribution networks are very useful for improving observability by acquiring system real-time data. However, three-phase imbalance and harmonic power flows adversely impact the accuracy of synchronous measurements, which implies the importance of phasor estimation errors. This paper proposes a new phasor estimation algorithm for mu PMU in active distribution networks that uses a conditional maximum likelihood (CML) estimation method. Firstly, the signal model of three-phase, three-wire and four-wire imbalance systems is established. Then, the probability distributions of the magnitude and phase angles are derived from the geometric characteristics of the CML method by solving the geometric equation. Simulation results show that the proposed CML based method is effective for estimating phasor and impedance models of active distribution networks by using mu PMU measurement data.