Journal of Modern Power Systems and Clean Energy

ISSN 2196-5625 CN 32-1884/TK

Reliability evaluation of modular multilevel converter based on Markov model
Author:
Affiliation:

1 School of Power Electric Engineering, Nanjing Institute of Technology, Nanjing 211167, China 2 State Key Laboratory of Intelligent Technology and Systems, Tsinghua University, Beijing 100084, China 3 School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China 4 State Grid Jiangsu Electric Power Company Xuzhou Power Supply Company, Xuzhou 221005, China 5 Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190, China

Fund Project:

This work was supported by the National Natural Science Foundation of China (No. 51607084), the National Key Research and Development Program of China (No. 2017YFB0903504), Jiangsu Electric Power Company Project (No. J2018076), State Grid Technology Project (No. 5210EF17002B) and the State Key Laboratory of Smart Grid Protection and Control.

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    Abstract:

    The modular multilevel converter (MMC) is now the most attractive topology for medium and high voltage power conversion applications with several advantages over the traditional voltage source converter (VSC). However, due to a large number of sub-modules (SMs) in the MMC, system reliability is a big challenge in its practical application, where each SM may be considered as a potential point of failure. In this paper, a reliability evaluation based on the Markov model is proposed for the MMC. The failure rates of the power electronic devices and SMs are firstly analyzed. Then, the Markov model and the state transition equation of the system are built in detail. A general reliability evaluation function is established, in which the mean time to failure and reliability evaluation of the MMC with redundant SMs are also discussed. Finally, a practical direct current (DC) distribution example for reliability evaluation is analyzed, and the results verify that the reliability evaluation based on the Markov model could provide a useful reference for project design.

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  • Received:
  • Revised:
  • Adopted:
  • Online: September 24,2019
  • Published: