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A Fast Method for Reliability Evaluation of Ultra High Voltage AC/DC System Based on Hybrid Simulation
- Source :
- IEEE Access, Vol 6, Pp 19151-19160 (2018)
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- The construction and operation of the ultrahigh voltage power grid has solved the problem of optimal allocation of energy resources and played a key role in promoting social development. However, concerns about its safety have kept growing in recent years. In order to analyze the reliability of ultrahigh voltage AC/DC system combined with the quasi-Monte Carlo method and PSD-BPA simulation, the reliability model of various components and system is established, and the simulation speed is improved with accuracy ensured. In order to ensure the compatibility and efficiency of the software, we design the BPA-Matpower data interface, and the data translation from BPA to Matpower is realized by fourth conversion. Then, we propose an index system for reliability evaluation, concise and easy to compute, to reflect the reliability of the UHV grids and the characteristics of AC and DC systems. Based on actual regional powergrid, we compare the model in this paper with the traditional sequential Monte Carlo method, and carry out the analysis of the component sensitivity to study the multi-fault characteristics and the weakness of the system, and verify the scientific and effective result of this paper.
- Subjects :
- General Computer Science
Computer science
020209 energy
Energy resources
Monte Carlo method
General Engineering
Ultra high voltage
data interface
02 engineering and technology
reliability evaluation
Reliability engineering
index system
Component (UML)
0202 electrical engineering, electronic engineering, information engineering
Key (cryptography)
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
Sensitivity (control systems)
Power grid
hybrid simulation
lcsh:TK1-9971
Reliability (statistics)
Voltage
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....9d1b8267f92518ced8bf5ff2ca08ebfb
- Full Text :
- https://doi.org/10.1109/access.2018.2817247