Failure Probability Model of Distribution Network Equipment Based on Improved Age-Reduction Model and Factor Correction

Abstract

Equipment outage is the root cause of power system failure, and the establishment of equipment failure rate model is the basis for system reliability analysis. Based on data-driven and fuzzy theory, a time-varying failure rate model of equipment was proposed. Firstly, double Weibull distribution was used to describe the aging failure. For the risk factors such as operating environment, internal health, external condition and meteorological environment, the equipment state was evaluated by subjective and objective comprehensive weight. The exposed equipment adopted the dual-condition cloud model, and the distribution of cloud drops was used to describe the impact factor. The enclosed equipment adopted the proportional hazard model and used comprehensive health index as the covariate. Secondly, considering repair fatigue, an improved age-reduction model was applied to calculate the equivalent age. Thirdly, using Levenberg Marquardt method to estimate the parameters of the model. Finally, the typical scenarios were extracted based on the improved k-means to calculate the reliability of a microgrid. The results show that the model can better simulate the actual situation of system operation, reflect the temporal and spatial differences of equipment failure, and improve the accuracy of reliability calculation.