Distribution System State Estimation Based on Multi-section Smart Meter Data

As a large number of distributed generation (DG), electric vehicles (EV), and energy storage systems (ESS) are connected to the distribution system, it is particularly important to conduct real-time distribution system state estimation. Current hybrid measurement of distribution system is mainly composed of Supervisory Control and Data Acquisition (SCADA) and Advanced Metering Infrastructure (AMI). Due to the cost restriction, the measurement redundancy of current distribution system is low. The information provided by any single type of measurement is difficult to make the distribution system state estimation meet the observable requirement. In addition, the low sampling frequency of AMI cannot realize the real-time distribution system state estimation. Regarding the above problems, this paper proposes an AMI pseudo measurement modeling method based on sliding time window, and introduces it into the hybrid measurement model of SCADA and AMI. During the non AMI sampling period, the AMI pseudo measurement is established through the multi-time section data fitting of the AMI sampling data in the sliding time window. It makes the distribution system of the non AMI sampling period more observable and shortens the execution cycle of the distribution system state estimation. The example is used to prove that the method realizes the high precision state estimation during the non AMI sampling period.