The invention provides an online risk assessment method for the influence of an intelligent isolation circuit breaker on a power grid based on big data analysis. Based on data of each component in theintelligent isolation circuit breaker, Current power grid operating state data, Power grid risk data, A Markov instantaneous state probability model of the intelligent isolation circuit breaker is obtained through environment data, a state distribution curve is constructed, the state probability model is sampled through a Latin hypercube algorithm, the state of the intelligent isolation circuit breaker is obtained, the matrix is rearranged through Cholesky decomposition, and the correlation of initial sampling is reduced. And using an OPF algorithm taking the minimum load shedding as an objective function to calculate the minimum value of the load shedding after the fault occurs and the risk index. Aiming at different faults in the intelligent isolation circuit breaker, the influence of different component faults on the risk degree of the power grid is obtained by calculating the sensitivity, and reference is provided for differential operation and maintenance.