In the scope of this work, a method capable of fast identification of the proper countermeasure, that prevents emerging instability, has been developed. The focus is placed on the prevention of aperiodic small signal angular instability by means of manipulations applied to load nodes (nodes containing no voltage sources). The main functionality of the early prevention method is to deliver control solution allowing escape from instability on the basis of data obtained by PMU measurements. The developed algorithm performs identification of the optimal node for countermeasure application and defines which amount of countermeasure would be sufficient to bring a critical generator to the stable operation. The early prevention method is addressing the possibility of near real time analysis, utilizing computationally efficient algorithms. The method is providing efficient countermeasure matching a given operational conditions and predicts the resulting stability margins for the new steady state, while avoiding time consuming time domain simulations. The method has been validated on the Western Danish power system model, containing 464 buses. The case study of aperiodic small signal angular instability was created. Utilizing synthetic PMU data, the early prevention method proposed a location and an amount of the countermeasure which will prevent instability; the prediction of the resulting stability margins corresponding to application of the suggested countermeasure was carried out. The predicted effect of the suggested countermeasure application is in a good agreement with the results obtained by RMS dynamic simulation. Developed method enables adaptive preventive control for near real-time stability maintenance. The achieved results are opening promising perspective for power system’s evolution to self-curing systems, for which the human factor involved in control, will keep diminishing.