Abstract: In recent years, the level and scale of power grid interconnection have developed rapidly, integration the uncertainty and the regulation and control requirement of the power system keep increasing with the large-scale integration of new energy and power electronic equipment. The current power grid regulation and control method has the problems such as dependence on the abnormal triggering of the experience characteristic quantity and the lack of the regulation and control means for proactivity and predictability based on the out-of-limit of the tie line. In order to solve the problems, a method of risk assessment and proactive regulation and control is proposed for power grid operation safety based on probability prediction. Firstly, a rolling probability prediction model based on long short-term memory（LSTM） network and support vector machine（SVM） is constructed. Then, the severity function of common risk events is established from the perspective of sufficiency to achieve the over-limit probability prediction of key elements. Also, the quantitative risk is calculated to form a trigger mechanism so that the proactive regulation and control of the power system for risk events is realized. Finally, a simulation is carried out on the IEEE 39-bus system combined with the actual load data of a certain provincial power grid in China. The calculation results verify that the proposed method and model can realize the proactive regulation and control in advance and effectively avoid the risks of safe operation.