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|Title:||Optimal PMU placement considering state estimation and voltage stability in smart grid||Authors:||Zhang, Chunxue||Degree:||Ph.D.||Issue Date:||2018||Abstract:||The 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.
In 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.
|Subjects:||Hong Kong Polytechnic University -- Dissertations
Electric power systems
Smart power grids
Supervisory control systems
|Pages:||xxii, 108, 17 pages : color illustrations|
|Appears in Collections:||Thesis|
View full-text via https://theses.lib.polyu.edu.hk/handle/200/9661
Citations as of May 29, 2022
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