Distributed-Dynamic State Estimation with SCADA and PMU

Distributed-Dynamic State Estimation with SCADA and PMU

Pietaloka, D.

Popov, M. (mentor)
Rueda Torres, J.L. (mentor)

Electrical Engineering, Mathematics and Computer Science

Electrical Power Engineering

2015-08-26

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 based DSE) with SCADA and PMU; and distributed –Unscented Kalman Filter based Dynamic State Estimation (distributed-UKF based DSE) with SCADA and PMU. As a comparison, the implementation of EKF-based DSE and UKF-based DSE 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.

state estimation
distributed
dynamic
EKF
UKF
PMU
SCADA

http://resolver.tudelft.nl/uuid:cbe7e928-c213-45d7-ac38-620b90705344

Student theses

master thesis

(c) 2015 Pietaloka, D.