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Enhancement of coherency identification techniques for power system dynamic equivalents
Authors: Sung-Kwan Joo; Jong-Woong Choe; Chen-Ching Liu;
Abstract
In dynamic studies of large electric power systems, it is often necessary to reduce a large power network to a smaller equivalent system while keeping the dynamic characteristics of the full system model within the desired accuracy. This paper proposes new coherency identification techniques using the K-means algorithm for construction of dynamic equivalent models. Numerical simulation results based on a NPCC 48-machine test system are presented to demonstrate the performance of the proposed method.
Related Organizations
- University of Mary United States
- Washington State University United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).11 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average

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citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
popularity
Popularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
11
Average
Top 10%
Average
Fields of Science (3) View all
Related to Research communities
Energy Research