Computationally efficient PMU-based L1 estimators for large power systems

Title:
Computationally efficient PMU-based L1 estimators for large power systems
Creator:
Xu, Chenxi (Author)
Contributor:
Abur, Ali (Advisor)
Amirabadi, Mahshid (Committee member)
Lehman, Brad (Committee member)
Language:
English
Publisher:
Boston, Massachusetts : Northeastern University, August 2018
Date Awarded:
August 2018
Date Accepted:
May 2018
Type of resource:
Text
Genre:
Dissertations
Format:
electronic
Digital origin:
born digital
Abstract/Description:
Phasor Measurement Units (PMUs) are increasingly deployed in power systems because of their nice characteristics like fast data acquisition rate and GPS clock synchronization. With the explicit usage of PMU measurements, Least Absolute Value (LAV) State Estimator (SE), together with its built-in Bad Data (BD) rejection capability, can be formulated as a Linear Programming (LP) problem and solved efficiently by high-performance LP solvers. This dissertation reviews the foundational research on power system state estimation and proposes several novel LAV SEs with high robustness and computational performance for Very Large Scale Interconnected (VLSI) power grids when the system is measured by only PMUs.

The first part of this dissertation presents two centralized LAV SEs incorporating Zero Injection (ZI) measurements into the LAV state estimation formulation using direct enforcement and Kron reduction, respectively.

Based on the current circumstance that VLSI power grids are usually divided into several independent and non-overlapping zones, the second part of this dissertation presents several multi-area distributed LAV SEs.

The first algorithm combines a well-known LP decomposition method: Dantzig-Wolfe (DW) decomposition with the LAV SE considering the motivation that LAV can be formulated as an LP problem and multi-area state estimation measurement matrix has the exact structure required by DW.

The second algorithm uses a two-stage set-up to assure adequate robustness around zone boundaries. All zones run their own SEs and the estimated boundary bus states, together with measurements between zones, are both used as measurements for the second stage SE run by a central coordinator.

The third algorithm generates one or several additional zones covering all boundary buses and their direct neighbors. This new zone and all existing zones run their SEs simultaneously in parallel. Results are collected and reconciled to provide a full set of state estimates.

The fourth algorithm creates one or several copies of the system. Each copy contains one way of system zone partitioning. All buses appear at least once as an internal bus in these copies. All zones in all copies run independent SEs. An algorithm is developed for the automatic copy generation.

The above multi-copy algorithm is implemented and further tested on a high-performance multi-core computer using parallel processing.

Above algorithms are implemented on different test systems with sizes ranging from 30-bus to 16216-bus and the corresponding simulation results are presented in this dissertation.
Subjects and keywords:
high-performance computing
linear estimation
parallel computation
phasor measurements
state estimation
DOI:
https://doi.org/10.17760/D20292599
Permanent Link:
http://hdl.handle.net/2047/D20292599
Use and reproduction:
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