Major faults arise in power converters mainly due to faulty MOSFET switches, diode and electrolyte capacitors. Converter with fault tolerant circuit improves the overall reliability of DC‐DC converter. We develop a self‐test configuration that identifies the faults in analog to digital converter (ADC), DC to DC converter and battery. IEEE 21451 standard‐based interface is implemented to develop a knowledge‐based smart controller. The centralized controller is performed to execute the maximum power point tracking (MPPT). Photovoltaic (PV) energy storage system is constructing to prove how the converter’s sensing, processing, and actuation capabilities in actual time may allow effective fault identification. The simulation result of the proposed method is executed in the MATLAB/Simulink working platform. The experimental results are implemented with field‐programmable gate array of Spartan‐6 Xilinx. The simulation as well as experimental result shows different fault identification in PV with energy storage system. Battery is provided through 12 V/4.5 Ah battery. The simulation and experimental results make ensure that the proposed method reveals its proficiency. It shows that the received results may fault identification at less than the period of one switching usually by 100 ms with suggested method.

中文翻译：

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基于IEEE21451标准的光伏储能系统组件故障识别与隔离

功率转换器中出现主要故障的主要原因是MOSFET开关，二极管和电解质电容器出现故障。具有容错电路的转换器提高了DC-DC转换器的整体可靠性。我们开发了一种自测配置，可以识别模数转换器（ADC），DC-DC转换器和电池中的故障。实施基于IEEE 21451标准的接口以开发基于知识的智能控制器。执行集中控制器以执行最大功率点跟踪（MPPT）。光伏（PV）能量存储系统正在构建中，以证明转换器在实时中的感应，处理和驱动能力如何能够有效地识别故障。该方法的仿真结果在MATLAB / Simulink工作平台上执行。实验结果通过Spartan-6 Xilinx的现场可编程门阵列实现。仿真和实验结果表明，储能系统在光伏系统中具有不同的故障识别能力。电池通过12 V / 4.5 Ah电池提供。仿真和实验结果确保了该方法的有效性。结果表明，采用建议的方法，接收到的结果可能在少于一次切换的时间（通常为100 ms）内进行故障识别。