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Content Provider | IEEE Xplore Digital Library |
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Author | Zhenyu Huang Ruisheng Diao Shuangshuang Jin Yousu Chen |
Copyright Year | 2014 |
Description | Author affiliation: Battelle Seattle Res. Center, Pacific Northwest Nat. Lab., Seattle, WA, USA (Shuangshuang Jin; Yousu Chen) || Electr. Infrastruct., Pacific Northwest Nat. Lab., Richland, WA, USA (Zhenyu Huang; Ruisheng Diao) |
Abstract | Traditional dynamic security assessment is limited by several factors and thus falls short in providing real-time information to be predictive for power system operation. These factors include the steady-state assumption of current operating points, static transfer limits, and low computational speed. This addresses these factors and frames predictive dynamic security assessment. The primary objective of predictive dynamic security assessment is to enhance the functionality and computational process of dynamic security assessment through the use of high-speed phasor measurements and the application of advanced computing technologies for faster-than-real-time simulation. This paper presents algorithms, computing platforms, and simulation frameworks that constitute the predictive dynamic security assessment capability. Examples of phasor application and fast computation for dynamic security assessment are included to demonstrate the feasibility and speed enhancement for real-time applications. |
Starting Page | 1 |
Ending Page | 5 |
File Size | 1058591 |
Page Count | 5 |
File Format | |
ISBN | 9781479964154 |
DOI | 10.1109/PESGM.2014.6938850 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-07-27 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Power system dynamics Security Real-time systems Computational modeling Mathematical model Equations State estimation RealTime Operation Dynamic Security Assessment Advanced Computing Phasor Measurement Predictive Capabilities |
Content Type | Text |
Resource Type | Article |
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