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Markov-based Reliability Analysis of Hybrid PCS: Evaluation of the Effect of Redundancy Design, PV Generation, and Power Demand
Author(s) -
Seong Jin Lim,
Sun-pil Kim,
Guangxu Zhou,
Feel-soon Kang
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3618839
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
A hybrid power conversion system (PCS) supplies power to the grid using power sources with different characteristics, such as photovoltaic (PV), energy storage system (ESS), and polymer electrolyte fuel cell (PEMFC). If the output of each power source is connected in parallel to the dc-link and a converter with the same power rating is used, a redundancy effect can be obtained. The operation of the hybrid PCS system is determined by the state of charge (SOC) of the ESS battery, and the operating power is determined by the PV generation and grid demand power or ESS battery charging demand power. In this paper, we design a Markov model that considers the reliability of the hybrid PCS, the operating mode, the operating power according to the PV generation and demand power, the operating power change due to partial failure, and the on-load and standby redundancy methods, and analyze the reliability along with the verification of the operation through simulation to present design guidelines for securing high reliability of the hybrid PCS system. The result of the reliability analysis based on an operating temperature of 50°C is that the standby method MTTF is 9.8% longer than the on-load method. Also, when PV generation exceeds demand power, the average lifespan is 23.4% longer than below the demand. When demand is 3 kW, the lifespan increases by 31.8% compared to 5 kW, and when demand is 1 kW, the lifespan increases by 12.1% compared to 3 kW.

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