A Hybrid State Estimator Based on SCADA and PMU Measurements for Medium Voltage Distribution System

Xiangyu Kong,Chengsi Yong,Tao Xu,Peng Li,Li Yu,Chengshan Wang,Ying Chen

doi:10.3390/app8091527

Abstract

With the increasing importance of renewable energy and flexible loads, the operation of the distribution system is becoming more stochastic and complex, and it is necessary to monitor the power system in real-time. Considering the gradual applications of intelligent electronic devices in the distribution systems, a hybrid state estimator based on supervisory control and data acquisition (SCADA) and phasor measurement unit (PMU) measurements is proposed in this paper, which consists of the improved robust estimation and linear state estimation. At the time of SCADA data acquisition, the improved robust estimation combining the SCADA measurements with PMU measurements is performed. To eliminate the effect of bad data, the internal student residual method is introduced, and the robust thresholds are adjusted adaptively. Then the linear state estimation is performed at the time of PMU data acquisition based on the results of the previous estimation time and the PMU measurements, which can quickly correct the robust estimation results and track the changes of the distribution system. Finally, the effectiveness and performance of the proposed method are verified in a modified IEEE 33-bus distribution system and a real distribution system in China.

Highlights

As more and more distributed generation (DG) and electric vehicles are connected to the distribution networks, the operational characteristics of the distribution system have been changed [1]
The proposed improved IGGIII (IIGGIII)-linear state estimation (LSE) could track the changes of the states, whose effect was similar to the method weighted least squares (WLS)-unscented Kalman filter (UKF)
To verify the robustness of the improved Institute of Geodesy and Geophysics III (IGGIII) at the supervisory control and data acquisition (SCADA) data acquisition time, the bad data were assumed to appear in the voltage amplitude at bus and the active power of branches data were assumed to appear in the voltage amplitude at bus 6 and the active power of branches 5–6

Summary

Introduction

The bidirectional power flow occurs when the generation from distributed units exceeds the local load, and the voltage profile of the distribution network will be influenced strongly. The network configuration of the smart distribution network will be changing dynamically to achieve minimum power loss and voltage deviations. The real-time monitoring of the distribution network is becoming more and more challenging due to the increasing dynamics and changing behavior of actors in distribution systems [2]. The operating condition needs to be perceived first and a key technology obtained to achieve the reliable and accurate system condition awareness is known as the distribution system state estimation (DSSE). The DSSE is used to calculate the real-time measurement data according to some optimal estimation criterion, improving the accuracy of the data and obtaining a credible state for the whole system.

Methods

Results

Conclusion