机译:通过使用稀疏自动编码器区分阵列故障和对称线路故障,提高光伏集成微电网保护方案的可靠性
Natl Inst Technol, Dept Elect Engn, Raipur, CG, India;
Natl Inst Technol, Dept Elect Engn, Raipur, CG, India;
Natl Inst Technol, Dept Elect Engn, Raipur, CG, India;
support vector machines; learning (artificial intelligence); decision trees; power generation protection; power engineering computing; neural nets; photovoltaic power systems; fault diagnosis; power generation faults; distributed power generation; power grids; unsupervised learning; PV integrated microgrid; symmetrical line faults; sparse auto encoder; photovoltaic integrated microgrid; reliable protection scheme; similar voltage-current profile; PV array faults; conventional protection schemes; sparse autoencoder; fault detection; SAE; deep neural network approach; array faults; fault classification; fault section identification; grey-scale image dataset; unsupervised feature learning; reliability analysis; artificial neural network; support vector machine; decision tree-based techniques; grid-connected mode; islanding mode; OPAL-RT digital simulator;
机译:II,III和IV风力涡轮机和PV集成杂交微电网系列和分流故障的识别和性质检测,具有模糊逻辑的自适应保护方案
机译:通过改进继电并区分逆变器故障和配电线路故障来增强光伏供电微电网的弹性
机译:基于稀疏自动编码器的深度神经网络方法用于感应电动机故障分类
机译:用于检测高阻抗故障的增强型MV微电网保护方案
机译:面对保护误操作的传输线故障的可扩展诊断方案。
机译:对称和非对称故障触发条件后自主微电网的性能分析
机译:用于增强电流保护方案的IEEE 14总线对称断层的分析
机译:基于稀疏性的集成电路光学故障分析中增强分辨率的框架。