Model-based hierarchical diagnosis method for distribution network faults

In order to solve the problems of model-based diagnosis method for distribution network faults, such as slow diagnosis speed, low accuracy and low fault tolerance in diagnosis of multiple multi-phase faults, a model-based hierarchical diagnosis method for distribution network faults is proposed. From the aspect of diagnosis algorithm, the new fitness function and the search strategy of feature learning are used to improve the diagnosis speed and accuracy. In the diagnosis model, the single-layered single high-dimensio-nal operations is transformed into two-layered multiple low-dimensional operations by a hierarchical approach, which further improves the diagnosis speed and accuracy. The fault tolerance ability of the first layer diagnosis is improved by defining the constraint relation of the equivalent components, and that of the second layer diagnosis is improved by using the redundancy relation of voltage constraints and current constraints. Numerical examples show that compared with other diagnosis methods, the speed of model-based hierarchical diagnosis method is greatly improved, the accuracy is always maintained near the ideal value, and the fault tolerance ability is obviously enhanced. In the fault diagnosis of large-scale distribution network, the model-based hierarchical diagnosis method has obvious advantages. © 2020, Electric Power Automation Equipment Press. All right reserved.