부산대학교 도서관

With the continuous progress of The Times and economic development, China's electric power industry is also undergoing profound changes. In the process of the continuous expansion of the scale of the power grid infrastructure construction project, the risk management for the safety of the infrastructure operation is becoming more and more important. This paper mainly studies the risk assessment of power grid infrastructure operation under the background of big data era. This paper first gives a systematic overview of risk management, and then builds a risk assessment model based on big data and random set theory. In this paper, the risk assessment model is used to evaluate the equipment risk and environmental risk in the operation of power grid infrastructure. In this paper, through the construction of the operation risk assessment model, various production risk factors are quantitatively evaluated, the key and high-risk factors of operation risk are determined, and the overall production risk level of infrastructure operation is obtained, which solves the subjective problem of risk assessment. This helps identify the failure modes and trends of power grid equipment. By analyzing historical data, typical fault modes of equipment can be identified, and a prediction model can be constructed using machine learning algorithms to predict potential future faults. In this way, power grid operators can take maintenance measures or replace equipment in advance to avoid the impact of faults on the power grid.