Multi-terminal lines impedance estimation
Level of difficulty:
MS Thesis – Student must register for ECE299.
Thesis Supervisor contact info:
Hassan Ghoudjehbaklou, Ph.D., PE, SMIEEE
Principal Engineer, Transmission Planning
San Diego Gas and Electric (SDG&E)
Instructor at UC San Diego (UCSD), UCSD Extension
IEEE: Senior Member, Chair of PES & PELS Chapters, San Diego Section
Line impedances are important parameters that are used in Planning, Protection Relaying, and operation control, among other areas, and their accuracies could impact day-to-day operating decisions. However, it is well understood that line impedances change under different transmission line loading and operating conditions, including climate changes.
On the other hand, in recent years, a large number of Phasor Measure Units (PMUs) have been deployed in power system utilities around the world. PMUs could provide power system measurements at high sampling rates. Due to limitation of equipment costs and required communication, at present, PMU measurements are mainly available in dense concentration at high voltage transmission systems, while deployment at distribution levels are very scattered.
With high sample rate voltage and current measurements coming from PMUs, the idea is that, one could potentially estimate the changing line impedances in real-time and utilize more accurate impedances in the operational studies and decisions.
MS Thesis research proposal:
The theory of impedance estimation for two terminal lines are straight forward and many researchers have worked on some variations of it. However, in each utility, several 230 kV lines might have 3-terminal configuration and some utilities might even utilize higher number of terminals for several of their 138 kV or 69 kV lines. The idea of this research project is to estimate line impedance of multi-terminal lines in real-time, using PMU measurements. The initial focus of this project would be 230 kV 3 -terminal lines.
Some power system knowledge, at the level of ECE121A, proficiency in Matlab programming, and strong background in control system & estimation theory, such as time series ARMA and Kalman filters, are required. (Student and professors involved in the project may have to sign a Non-Disclosure Agreement, NDA, to not disclose the data in any form without prior written approval from the thesis supervisor.)