2019
DOI: 10.1109/access.2019.2949507
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Enabling Model-Based LTI for Large-Scale Power System Security Monitoring and Enhancement With Graph-Computing-Based Power Flow Calculation

Abstract: The voltage stability is an essential security concern when a system is operating in peak load hours or subjected to an N-1 contingency. Among various voltage stability indices, Local Thevenin Index (LTI) has been a popular one, but mostly applied to the measurement-based framework. The reason is that it requires significant computing effort if applied to model-based approach, even though the model-based LTI calculation can provide more accurate results. In this paper, a new model-based LTI calculation is prop… Show more

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Cited by 7 publications
(3 citation statements)
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“…The graph-based approach showed significant enhancement over speedup over a conventional MIP solution method on a Tigergraph v2.51 database. Similar applications of noSQL were explored in other power system studies [196,197,198].…”
Section: State Of the Artmentioning
confidence: 94%
“…The graph-based approach showed significant enhancement over speedup over a conventional MIP solution method on a Tigergraph v2.51 database. Similar applications of noSQL were explored in other power system studies [196,197,198].…”
Section: State Of the Artmentioning
confidence: 94%
“…[17] - [19]. In recent years, graph computing has also been extended to solve power system problems such as distribution network reconfiguration, parallel power flow calculation, and real-time EMS development [20]- [22]. With the development of a graph database (GDB) and graph models for parallel computing, more complex problems can be entirely solved using graph-based methods and achieve better overall computing performance [23] - [25].…”
Section: Introductionmentioning
confidence: 99%
“…Some considerations were made recently to improve scalability of some methods in the literature. like in [18][19][20], where the focus is large systems scalability and reduced computational burden by using parallel and high performance computing. System partitioning was made using graph methods to facilitate parallel computation using fast-decoupled power flow method.…”
Section: Introductionmentioning
confidence: 99%