A High Performance Computational Framework for Dynamic Security Assessment under Uncertainty

被引：0

作者：

Chen, Yousu ^{[1
]}

Palmer, Bruce ^{[2
]}

Sharma, Poorva ^{[3
]}

Yuan, Yong ^{[4
]}

Mathew, Bibi ^{[3
]}

Huang, Zhenyu ^{[1
]}

机构：

[1] Pacific Northwest Natl Lab, Elect Infrasture & Bldg, Richland, WA 99352 USA

[2] Pacific Northwest Natl Lab, High Performance Comp, Richland, WA 99352 USA

[3] Pacific Northwest Natl Lab, Data Architectures, Richland, WA 99352 USA

[4] Pacific Northwest Natl Lab, Hydrol, Richland, WA 99352 USA

来源：

CONFERENCE RECORD OF THE THIRD IEEE INTERNATIONAL WORKSHOP ON ELECTRONIC POWER GRID (EGRID) | 2018年

关键词：

dynamic security assessment; high-performance-computing; uncertainty; smart sampling; middleware; visualization; GRIDPACK(TM);

D O I：

暂无

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Dynamic security assessment (DSA) is a critical function to evaluate power grids' capability to survive the transition caused by a set of disturbances to an acceptable steady-state condition. Its computational burden is heavy. With the challenges brought by renewable energy and new smart grid technologies, DSA under uncertainty has to be considered to study the impact of forecast errors on DSA simulation, which further increases the computational burden. To address this challenge, this paper presents a high performance computational framework to support DSA simulation user uncertainty. The computational framework provides a seamless work flow that links data from high performance computing, statistical analysis, to visualization so that a problem can he easily expressed in a way compatible with different functions. It also enables software compatibility such that application development can be more efficient. Case study results of the ESCA60 system and a western U.S. system show the advantages and efficiency of the computational framework.

引用

页码：31 / 35

页数：5

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