Cause-Effect Modeling and Spatial-Temporal Simulation of Power Distribution Fault Events

Modeling and simulation are important tools in the study of power distribution faults due to the limited amount of actual data and the high cost of experimentation. Although a number of software packages are available to simulate the electrical signals, approaches for simulating fault events in different environments have not been well developed. In this paper, we propose a framework for modeling and simulating fault events in power distribution systems based on environmental factors and the cause-effect relationships among them. The spatial and temporal aspects of significant environmental factors leading to various faults are modeled as raster maps and probability functions, respectively. The cause-effect relationships are expressed as fuzzy rules and a hierarchical fuzzy inference system is built to infer the probability of faults in the simulated environments. A test case simulating a part of a typical city's power distribution systems demonstrates the effectiveness of the framework in generating realistic distribution faults. This work is helpful in fault diagnosis for different local systems and provides a configurable data source to other researchers and engineers in similar areas as well.