Application of knowledge graph in smart grid fault diagnosis

Fault-diagnosis of grid structures

The problem of fault diagnosis in grid-connected systems is considered. A diagnosis algorithm, called DAGS and based on the PMC model, is presented. DAGS provides a diagnosis which is shown to be correct, although possibly incomplete, if the cardinality of the actual fault set is below a bound Tσ, dependent of the actual syndrome σ. A bound T independent of σ is also derived by a worst-case ana...

Grid Application Fault Diagnosis Using Wrapper Services and Machine Learning

With increasing size and complexity of Grids manual diagnosis of individual application faults becomes impractical and timeconsuming. Quick and accurate identification of the root cause of failures is an important prerequisite for building reliable systems. We describe a pragmatic model-based technique for application-specific fault diagnosis based on indicators, symptoms and rules. Customized ...

General Application of Smart Inverters in Distribution and Smart Grid

Application of Radial Basis Neural Networks in Fault Diagnosis of Synchronous Generator

This paper presents the application of radial basis neural networks to the development of a novel method for the condition monitoring and fault diagnosis of synchronous generators. In the proposed scheme, flux linkage analysis is used to reach a decision. Probabilistic neural network (PNN) and discrete wavelet transform (DWT) are used in design of fault diagnosis system. PNN as main part of thi...

Fault Recovery Algorithm for WSNs in Smart Grid

—A large number of sensors are deployed in smart grid for monitoring and metering of the power equipment and other key facilities as well as users’ behavior. The collected information is sent to data processing center for analyzing and processing. Because of the relatively complicated and harsh working conditions of sensors in smart grid, sensor fault occurs frequently. To ensure the normal ex...