The outage of equipment is the root cause of the failure of power system, so building a failure probability model for equipment is the key to the risk assessment of system. Based on internal and external mechanism which will lead to failure, this paper proposes ‘Ageing-Load-Health-Weather-PHM (ALHW-PHM)’, which is for risk assessment and applicable to characterize the failure probability of transmission lines. This model adopts temperature-based aging model as the baseline hazard function, and utilizes the wire real-time temperature which depends on load rate and the deterioration score deduction which depends on health status and weather condition as covariates in the link function. The maximum likelihood estimation (MLE) is used to estimate the model’s parameters. In order to improve the efficiency, a structure of parallel parameter estimation for samples basing on big data platform is designed. The case study quantitatively shows the impact of different risk factors and the application of failure probability in the risk assessment of power system. This model, which comprehensively considers the influence of risk factors such as thermal aging process, load factor, health status and weather conditions, can provide theoretical support for risk assessment. This work is supported by National High-tech R & D Program of China (863 Program) (No. 2015AA050204) and Zhejiang Provincial Natural Science Foundation (No. LZ14E070001).