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PMU-based State Estimation for Hybrid AC and DC Grids
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. (SmarTS Lab)ORCID iD: 0000-0002-2845-8043
2018 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Power system state estimation plays key role in the energy management systems(EMS) of providing the best estimates of the electrical variables in the grid that arefurther used in functions such as contingency analysis, automatic generation control,dispatch, and others. The invention of phasor measurement units (PMUs) takes thepower system operation and control into a new era, where PMUs’ high reportingrate and synchronization characteristics allow the development of new wide-areamonitoring, protection, and control (WAMPAC) application to enhance the grid’sresiliency. In addition, the large number of PMU installation allows the PMU-onlystate estimation, which is ready to leap forward today’s approach which is based onconventional measurements.At the same time, high voltage direct current (HVDC) techniques enable totransmit electric power over long distance and between different power systems,which have become a popular choice for connecting variable renewable energy sourcesin distant locations. HVDCs together with another type of power electronic-baseddevices, flexible AC transmission system (FACTS), have proven to successfullyenhance controllability and increase power transfer capability on a long-term costeffectivebasis. With the extensive integration of FACTS and HVDC transmissiontechniques, the present AC networks will merge, resulting in large-scale hybrid ACand DC networks. Consequently, power system state estimators need to considerDC grids/components into their network models and upgrade their estimationalgorithms.This thesis aims to develop a paradigm of using PMU data to solve stateestimations for hybrid AC/DC grids. It contains two aspects: (i) formulating thestate estimation problem and selecting a suitable state estimation algorithm; (ii)developing corresponding models, particularly for HVDCs and FACTS.This work starts by developing a linear power system model and applying thelinear weighted least squares (WLS) algorithm for estimation solution. Linear networkmodels for the AC transmission network and classic HVDC links are developed. Thislinear scheme simplifies the nonlinearities of the typical power flow network modelused in the conventional state estimations and has an explicit closed-form solution.However, as the states are voltage and current phasors in rectangular coordinates,phasor angle is not an explicit state in the modeling and estimation process. Thisalso limits the linear estimators’ ability to deal with the corrupt angle measurementsresulting from timing errors or GPS spoofing. Additionally, it is cumbersome toselect state variables for an inherently nonlinear network model, e.g., classic HVDClink, when trying to fulfill its linear formulation requirement.In contrast, it is more natural to use PMU measurements in polar coordinatesbecause they can provide an explicit state measurement set to be directly used inthe modeling and estimation process without form changes, and more importantly,it allows detection and correction for angle bias which emerges due to imperfectsynchronization or incorrect time-tagging by PMUs. To this end, the state estimationproblem needs to be formulated as a nonlinear one and the nonlinear WLS is applied for solution. We propose a novel measurement model for PMU-based state estimationwhich separates the errors due to modeling uncertainty and measurement noise sothat different weights can be assigned to them separately. In addition, nonlinearnetwork models for AC transmission network, classic HVDC link, voltage sourceconverter (VSC)-HVDC, and FACTS are developed and validated via simulation.The aforementioned linear/nonlinear modeling and estimation schemes belongto static state estimator category. They perform adequately when the system isunder steady-state or quasi-steady state, but less satisfactorily when the system isunder large dynamic changes and the power electronic devices react to these changes.Testing results indicate that additional modeling details need to be included toobtain higher accuracy during system dynamics involving fast responses from powerelectronics. Therefore, we propose a pseudo-dynamic modeling approach that canimprove estimation accuracy during transients without significantly increasing theestimation’s computational burden. To illustrate this approach, the pseudo-dynamicnetwork models for the static synchronous compensator (STATCOM), as an exampleof a FACTS device, and the VSC-HVDC link are developed and tested.Throughout this thesis, WLS is the main state estimation algorithm. It requiresa proper weight quantification which has not been subject to a sufficient attentionin literature. In the last part of thesis, we propose two approaches to quantify PMUmeasurement weights: off-line simulation and hardware-in-the-loop (HIL) simulation.The findings we conclude from these two approaches will provide better guidancefor selecting proper weights for power system state estimation.

Place, publisher, year, edition, pages
KTH Royal Institute of Technology, 2018. , p. 123
Series
TRITA-EECS-AVL
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-224445ISBN: 978-91-7729-723-9 (print)OAI: oai:DiVA.org:kth-224445DiVA, id: diva2:1191306
Public defence
2018-04-12, F3, Lindstedtsvägen 26, Stockholm, 10:00 (English)
Opponent
Supervisors
Funder
SweGRIDS - Swedish Centre for Smart Grids and Energy Storage, 761651
Note

QC 20180319

Available from: 2018-03-19 Created: 2018-03-17 Last updated: 2018-03-19Bibliographically approved

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