Loading...

Dynamic State Estimation in Power Systems Using Wide Area Measurement System (WAMS) Data

Mahdi Yousef, Mostafa | 2022

201 Viewed
  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54940 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Parniani, Mostafa
  7. Abstract:
  8. In the early days of implementing state estimation in power systems, only the steady-state and quasi-steady-state models of the system were considered for formulating the state estimation problem, accordingly called, Static State Estimation (SSE). However, after a few decades, with the growing diversity of power system components and complexity of its dynamic phenomena, uncertainty in the power system has dramatically increased. Consequently, the need for situational awareness of the dynamic states of the system (such as rotor angle and speed of the generators) is felt more than ever. In addition, occurrence of the catastrophic blackouts in the world owing to deficiency in dynamic monitoring abilities, have increased the motivation for enabling dynamic monitoring capabilities in the power system, mainly though implementing Dynamic State Estimation (DSE) using high-rate-sampled and synchronized measurements of the Phasor Measurement Units (PMUs) in the modern Energy Management System (EMS). Phasor measurement units, which are the most prominent components of the Wide Area Measurement System (WAMS), in contrast to Supervisory Control And Data Acquisition systems (SCADA) corresponded measurement devices, provide more accurate measurements with higher sampling rates. Also, the measured values have a time-stamp by resorting to Global Positioning System (GPS). Moreover, besides the magnitude of bus voltages and branch currents, their phase angles are measured continuously. Thus, estimating the dynamic state using WAMS data can provide reliable and invaluable dynamic information required by other functions of the modern EMS such as Dynamic Security Assessment (DSA) and periodical model validating, to name a few. In this thesis, we will propose a joint DSE using the combination of Robust Two-Stage Unscented Kalman Filter (UKF) and Robbins-Monro technique, which has more divergence speed and accuracy with respect to the existing schemes for DSE in the power systems. In addition to its robustness against pseudo-input and output outliers in a decentralized DSE scheme, the proposed method can validate the models and estimate the dynamic states, simultaneously. The performance of the proposed algorithm will be validated by using a prevalent test system for angle stability studies, i.e., the two area four machine test system. The proposed method paves the way for further studies about DSE effectiveness on the other applications e.g., evaluating performance of excitation systems and power system stabilizers, during faults occurrence
  9. Keywords:
  10. Wide Area Measurement System ; Kalman Filters ; Energy Management System ; Parameter Estimation ; Phasor Measurement Unit ; Power System Dynamic Monitoring ; Dynamic State Estimation

 Digital Object List

 Bookmark

No TOC