Two-stage interval state estimation method for AC/DC distribution systems based on SCADA and μPMU data fusion

AC/DC power distribution systems are emerging as a prevalent approach to accommodate the increasing prevalence of distributed energy resources and flexible loads. Meanwhile, the data environment of distribution networks is in a state where multi-source measurement information coexists. Under this background, this paper proposes a two-stage interval state estimation method for AC/DC distribution systems based on SCADA and µPMU data fusion. Firstly, addressing the issues of transmission delay and asynchronous sampling in the process of SCADA and µPMU data fusion, a data fusion method based on the correlation coefficient method and minimum time deviation is proposed. Secondly, aiming at the influence of measurement error, this paper constructs the measurement interval according to the maximum allowable error of different measuring devices. Simultaneously, pseudo-measurements are formulated in accordance with the control parameters of VSC. Finally, the AC/DC distribution system is redivided according to the VSC control mode, and a two-stage interval state estimation algorithm is proposed. This method achieves comprehensive state estimation across the entire network through one-way transmission of boundary information once, exhibiting high efficiency. The feasibility and effectiveness of the method in this paper are verified by the AC/DC distribution system built through simulation.