Distributed-Dynamic State Estimation with EKF and UKF in PMU at SCADA Systems

Publish Year: 1397
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:

ELEMECHCONF05_306

تاریخ نمایه سازی: 21 خرداد 1398

Abstract:

The purpose of this research is mainly to develop a distributed dynamic state estimation with PMU and SCADA as a response of the challenges in state estimation problems (accuracy, computational time, the use of new technology along with the ability to keep the existing traditional measurement). With the implementation of statistical signal processing technique into state estimation algorithm, this research conducts two different state estimation algorithms: distributed Extended Kalman Filter based Dynamic State Estimation (distributed-EKF) with SCADA and PMU; and distributed –Unscented Kalman Filter based Dynamic State Estimation (distributed-UKF) with SCADA and PMU. As a comparison, the implementation of EKF and UKF in integrated system has also performed. Variations number of PMU is installed in different buses location to see the effects on the state estimation result of the particular algorithms. The performance of the algorithm is studied using computer simulations and the comparisons are observed and analysed. The result of the simulation has shown that UKF-based DSE is a promising method in a nonlinear model implementation, although the difference with EKF-based DSE is small in this research. The result has also shown that more number of PMU installed give more state estimation accuracy for both algorithms. The concept of distribution state estimation has improved the performance of the state estimation in terms of efficiency (computational time) compare to integrated state estimation. The electrical network measurements by measuring device Phasor Measurement Device (PMU) are usually sent to the control centers using data acquisition system and other communication protocols available. However, these measurements contain uncertainties due to the measurements and communication noise (errors), incomplete metering or unavailability of some of measurements. The overall aim of state estimation is to calculate the state variables of the power system by minimizing errors available at the control center. Due to generate desired quantities by optimal estimate which is given the set of measurements, Kalman filters are widely used.

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Authors

Hamed Heydarifar

Iran University Of Science And Technology

Nasim Karimi Roozbahani

Iran University Of Science And Technology