论文标题
使用机器学习方法的DED逆变器的集成故障诊断和控制设计
Integrated Fault Diagnosis and Control Design for DER Inverters using Machine Learning Methods
论文作者
论文摘要
本文采用有监督的机器学习（ML）算法来提出集成的故障检测和诊断（FDD）和容忍故障控制（FTC）策略，以检测，诊断和对网格故障进行分类并纠正输入电压，然后再影响网格连接的分布能源资源（DER）Inverter。该控制器可以通过预测和修改输入电压的时间序列来减轻网格故障对逆变器的影响。仿真结果显示了拟议的控制器的有效性并评估其操作性性能。
This paper employs a supervised machine learning (ML) algorithm to propose an integrated fault detection and diagnosis (FDD) and fault-tolerant control (FTC) strategy to detect, diagnose, and classify the grid faults and correct the input voltage before affecting the grid-connected distributed energy resources (DER) inverters. This controller can mitigate the impact of grid faults on inverters by predicting and modifying the time series of their input voltage. Simulation results show the effectiveness of the proposed controller and evaluate its operating performance.
