Novel Approach for Fault Diagnosis of the Power Grid With Information Fusion of Multi-data Resources
Novel Approach for Fault Diagnosis of the Power Grid With Information Fusion of Multi-data Resources
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发表时间：
2009
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通讯作者：
G. Chuangxin;Peng Ming-wei;Liu Yi
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作者：
G. Chuangxin;Peng Ming-wei;Liu Yi
当电网发生故障时，故障信息主要由数字信息和模拟信息两部分组成。数字信息反映了继电器和断路器的状态，大多数故障诊断方法都利用这些信息。模拟信息是关于电压和电流的暂态值和波动。模拟信息可以准确地描述电网故障的性质。然而，很少有故障诊断方法利用这些数据资源。提出了一种新的故障诊断方法，即基于改进D-S理论（IMFD）的多数据资源与数字和模拟信息的信息融合。通过模糊Petri网将数字信息转换为模糊故障程度，通过小波分析将模拟信息转换为小波故障特征。然后利用改进的D-S证据理论进行信息融合故障诊断。最后，采用c均值算法对故障元素进行识别。仿真结果表明，该方法可以提高电网故障诊断的准确性和实时性。
The fault information mainly consist of two parts, the digital part and the analogue one, when the power grid is malfunctioning. The digital information reflects the status of relays and circuit breakers by which most methods for fault diagnosis utilize this information. The analogue information is about the transient value and the wave of voltage and current. The analogue information can accurately describe the properties of failure in the power grid. However, few methods for fault diagnosis use this data resource. A new fault diagnosis method, i.e. information fusion of multi-data resources in fault diagnosis based on improved D-S theory (IMFD) with digital and analogue information is presented. The digital information is transformed to fuzzy fault degree through fuzzy Petri nets and the analogue information is transformed to wavelet fault characteristics through the wavelet analysis. Then fault diagnosis is conducted based on information fusion with the improved D-S evidence theory. Finally, the fault element is identified with C-mean algorithm. Simulation results indicate that the proposed method can improve the accuracy and the real-time performance of fault diagnosis in the power grid.