DOI:10.1007/s40565-017-0354-4 |
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A modular parallelization framework for power flow transferanalysis of large-scale power systems |
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Net amount: 831 |
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Author:
Chuntian CHENG1
, Bin LUO1,2, Jianjian SHEN1
, Shengli LIAO1
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Author Affiliation:
1. Institute of Hydropower System and Hydroinformatics,
Dalian University of Technology, Dalian 116024, China
2. Tsinghua Sichuan Energy Internet Research Institute,
Chengdu 610200, China
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Foundation: |
This work was supported by the Major International
Joint Research Project from the National Nature Science
Foundation of China (No. 51210014) and Major Program of National
Natural Science Foundation of China (No. 91547201). |
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Abstract: |
Power flow transfer (PFT) analysis under various
anticipated faults in advance is important for securing
power system operations. In China, PSD-BPA software is
the most widely used tool for power system analysis, but its
input/output interface is easily adapted for PFT analysis,
which is also difficult due to its computationally intensity.
To solve this issue, and achieve a fast and accurate PFT
analysis, a modular parallelization framework is developed
in this paper. Two major contributions are included. One is
several integrated PFT analysis modules, including
parameter initialization, fault setting, network integrity
detection, reasonableness identification and result analysis.
The other is a parallelization technique for enhancing
computation efficiency using a Fork/Join framework. The
proposed framework has been tested and validated by the
IEEE 39 bus reference power system. Furthermore, it has
been applied to a practical power network with 11052
buses and 12487 branches in the Yunnan Power Grid of
China, providing decision support for large-scale power
system analysis. |
Keywords: |
Power flow transfer, Modular, Parallelization,
Fork/Join framework, PSD-BPA |
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Online Time:2018/07/20 |
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