一种考虑共线测量和高杠杆点的状态估计增量仪表放置方法

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
H. G. Abood, V. Sreeram, Yateendra Mishra
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引用次数: 3

摘要

摘要电力系统状态估计的性能受到电表配置和测量冗余度的影响。因此,需要通过安装新的SCADA仪表和相量测量单元来更新测量集,以提高SE解决方案的质量。但是,应该解决现有仪表和新仪表之间潜在的不一致。否则,额外的仪表可能导致数值问题,如共线性(由于重复测量造成的线性依赖)和高杠杆点(有影响的测量)的存在。因此,本文提出了一种增量式仪表放置方法。该方法利用了hlp,旨在提高SE的数值性能,并有助于消除不良数据。采用布谷鸟搜索优化法选择新米的最佳位置和数量。在英国18总线、IEEE 30总线和118总线系统上测试了该算法的性能,仿真结果表明该算法的质量有所提高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An incremental meter placement method for state estimation considering collinear measurements and high leverage points
Abstract The performance of the power system state estimation (SE) is influenced by the configuration of the meters and measurement redundancy. Therefore, the measurement set needs to be updated by installing new SCADA meters and phasor measurement units for improving the quality of the SE solution. However, the potential inconsistency between the existing meters and the new meters should be addressed. Otherwise, the additional meters may lead to numerical problems such as collinearity (linear dependence due to duplicated measurements) and the existence of high leverage points (HLPs) (influential measurements). Hence, this paper proposes an incremental meter placement method. The proposed method utilizes the HLPs and aims to improve the numerical performance of the SE and facilitate the elimination of bad data. The cuckoo search optimization is used for selecting the optimal locations and the numbers of the new meters. The performance of the proposed algorithm is tested on UK 18-bus, the IEEE 30-bus, and 118-bus systems and simulation results show improvements in the quality of the SE solution.
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来源期刊
CiteScore
2.70
自引率
8.30%
发文量
15
审稿时长
8 weeks
期刊介绍: nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity
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