Status : Verified
|Personal Name||Santos, Ren Zedec S.|
|Resource Title||Distribution system state estimator using SCADA and µPMU measurements|
|Date Issued||30 June 2018|
|Abstract||Under the context of distribution systems, a state estimator which utilizes both SCADA and µPMU measurements is considered the most beneficial form of state estimation. Individually, hybrid and multistage state estimators are only able to address few out of the many issues of state estimation. The configuration used in this paper utilizes both SCADA and µPMU measurements to both be used by a Weighted Least Squares (WLS) and a Weighted Least Absolute Values (WLAV) Estimation for the first stage and then combined using Multisensor Data Fusion (MDF) on the second stage.
Results of the WLS estimator presented in this paper show that a limited number of µPMUs on a distribution network on top of SCADA can improve the overall performance of distribution system state estimation by giving a more accurate, and reliable result. The huge difference of sampling rates of each measurement is also resolved by utilizing only one sample of each per estimation.
The results of the WLAV estimator presented in this paper show that the WLAV state estimator gave more accurate and more robust results compared to the WLS state estimator when the system is under a False Data Injection (FDI) attack. FDI attacks are used to test the robustness of the WLAV as comapred to the WLS estimator. Results show that, given the right information, the attacker can do this type of analysis first and then choose the right combination of measurements to attack in order to ensure an impact on the overall estimate. Nevertheless, even the worst results of the WLAV state estimator under multiple FDI attacks are still better than the result of the WLS state estimator under a single FDI attack. An FDI attack on a µPMU makes the WLS state estimator diverge whereas the WLAV detects it with some affected nearby buses. Countermeasures were tested on the WLAV and the recommended choice is to replace the attacked measurement by a pseudomeasurement. A linear programming formulation of WLAV (LP-WLAV) was used on the Fusion estimator because of its faster processing time than the previous WLAV formulation. The Fusion state estimator has shown more accurate and robust estimate compared to its parts – the WLS and LP-WLAV state estimators. This configuration also adds robustness against bad data and FDI attacks to the overall estimate. Dynamic state estimation is also possible under this configuration because of the fast processing time of the LP-WLAV and Fusion state estimator. This state estimator configuration which provides robustness against bad data and sub-second results is a promising solution when a limited number of µPMUs are introduced in a distribution system.
|Degree Course||Master of Science in Electrical Engineering|
|Keyword||State Estimator, WLS, WLAV, MDF, µPMU, SCADA|