Out-of-step detection of synchronous generators using dual computational techniques based on correlation and instantaneous powers

To maintain synchronous operation of interconnected systems, it is necessary to keep balance between power generation and consumption. Faults may result in large oscillations in power flows and loss-of-synchronism between one generator and the rest of the power system. A correlation coefficient is a useful statistic that can be used to detect voltage, frequency or angular instabilities, and to determine an asynchronous process. Hence, it is a smart technique to predict the out-of-step event following fault situations. In this paper, the technique based on the auto/cross-correlation and instantaneous powers is presented to identify sudden disturbances of various electrical signals in the case of asynchronous operation. To validate the method performance, a power network with real parameters is simulated on Alternative Transient Program (ATP) platform, and the algorithm is implemented in MATLAB software. Simulation studies reveal that the proposed scheme is able to detect the out-of-step conditions upon which the relay issues a trip signal, yet remains inactive under normal synchronized operating conditions. Thus, the out-of-step is declared before the second pole slipping occurs, and an instability time can be accurately assessed. Moreover, it can develop novel quadrilateral operating characteristics to discriminate between the synchronous and asynchronous operation of the AC generator.