Full metadata record
DC FieldValueLanguage
dc.contributorDepartment of Electrical Engineeringen_US
dc.contributor.advisorXu, Zhao (EE)-
dc.contributor.advisorChan, Ka Wing (EE)-
dc.creatorZhang, Chunxue-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/9661-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleOptimal PMU placement considering state estimation and voltage stability in smart griden_US
dcterms.abstractThe development of monitoring technologies in smart grid is undergoing an essential transition from SCADA to WAMS, which means the periodical magnitude-based measurement by RTU is gradually replaced by real-time PMU-based measurement. The implementation of PMUs can substantially facilitate grid-wide state estimation, stability analysis, and many other applications, which are dependent on an effective PMU placement strategy. Typically, Optimal PMU Placement (OPP) problem concerns problem finding the minimum number and the best location of PMUs to make the entire system observable. However, many other important benefits concerning state estimation, voltage stability and control were not properly considered. Particularly, dynamic voltage stability is a key operation index of smart grid and its assessment can largely benefit from PMUs, which however, has not been investigated thoroughly. In addition, earlier studies of OPP problems only focus on network topology yet neglect the effect of different operating scenarios, thus may lead to biased solution.en_US
dcterms.abstractIn this thesis, a comprehensive study is conducted to develop innovative and cost-effective OPP approaches, which can help to mitigate voltage estimation uncertainty and/or provide guidance for voltage stability assessment and control from both static and dynamic perspectives. The need of effective and efficient OPP approaches is highlighted in Chapter 1, where research background and overview of existing works about OPP are also presented. The limitation of existing approaches is also identified. Motivated by previous works, a channel-oriented OPP approach aiming at global observability is proposed in Chapter 2. Since not only the placement of PMU base unit, but also the allocation of channel is to be optimized, the investment can be further reduced. The measurement redundancy of each bus can be set in advance depending on the requirement of planning. To explore other potential benefits of WAMS, a new OPP regime considering mitigating voltage estimation uncertainty as well as providing guidance for zonal voltage control is proposed in Chapter 3. In this regime, the conventional OPP problem is converted to a multi-objective network partitioning problem, in which the optimal partitions find clusters with minimum voltage estimation uncertainty and maximum voltage changing consistency in a static sense. Moreover, probabilistic load flows (PLFs) are deployed to represent various operating scenarios. In this way, the time-changing load patterns and power generations are considered stochastically as the operating uncertainties, so that the obtained PMU placement solution is unbiased for planning purpose. Since voltage stability is a key operation index of power system and essentially a dynamic characteristic, in Chapter 4, a novel methodology is explored toward evaluating grid-wide voltage small signal stability in a dynamic sense. Then observability-based OPP approach is employed aiming to provide 1-time monitoring backup to the voltage-vulnerable buses, which are determined through the proposed stability assessment method. Similarly, to achieve a general planning solution, various operating scenarios are generated by sequential Monte Carlo simulation. The experiment on test case and the dynamic simulation results validate the effectiveness of the proposed approach. It is concluded in Chapter 5 that the proposed OPP approaches can effectively monitor the voltage stability in both static and dynamic sense, thus can provide quick and correct guidance for voltage regulation. Meanwhile, future works that can further extend this study are also indicated in Chapter 5.en_US
dcterms.extentxxii, 108, 17 pages : color illustrationsen_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2018en_US
dcterms.educationalLevelPh.D.en_US
dcterms.educationalLevelAll Doctorateen_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.LCSHElectric power systemsen_US
dcterms.LCSHSmart power gridsen_US
dcterms.LCSHSupervisory control systemsen_US
dcterms.accessRightsopen accessen_US

Files in This Item:
File Description SizeFormat 
991022165759403411.pdfFor All Users4.26 MBAdobe PDFView/Open


Copyright Undertaking

As a bona fide Library user, I declare that:

  1. I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
  2. I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
  3. I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.

By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.

Show simple item record

Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/9661