Effective identification of important nodes in power system is helpful to improve robustness of system and reduce the probability of accidents by applying additional protection or changing the topology of important nodes under limited resources. Inspired by the web page sorting algorithm, an algorithm called E-SALSA (electrical stochastic approach for link structure analysis) was proposed for evaluating important nodes in power system. Taking into account the influence of power system topology, power flow and other factors on nodes, this algorithm can effectively reflect the true situation of power system, and its features are more in line with the background of power system. In the IEEE300 node power system, the E-SALSA algorithm was compared with the electrical median algorithm and the MBCC-HITS (model based on co-citation hypertext induced topic search) algorithm by using the two indexes of the scale of load loss and the maximum subgroup size. The results show that the E-SALSA algorithm has advantages over electrical median algorithm in both indicators. Compared with MBCC-HITS algorithm, E-SALSA algorithm can use all factors more comprehensively on the impact of nodes, which further proves its rationality and effectiveness.