Setting and Testing of the Out-of-Step Protection at Mongolian Transmission System

Modern distance relays have integrated numerous protection functions, including power-swing blocking and out-of-step or pole-slip tripping functions. The main purpose of the power-swing blocking function is to differentiate faults from power swings and block distance or other relay elements from operating during stable or unstable power swings. Most power-swing blocking elements are based on traditional methods that monitor the positive sequence impedance rate. The required settings for the power-swing blocking elements could be difficult to calculate in many applications, particularly those where fast swings can be expected. For these cases, extensive stability studies are necessary to determine the fastest rate of possible power swings. This paper presents a detailed step-by-step method for settings calculation of out-of-step (OOS) protection, both blocking and tripping functions considering a generic two-source system. Then the method is applied to define the protection relay settings installed at the interconnection between the Russian and Mongolian power systems, as it is crucial to feed the demand-rich Mongolian power system. In this paper, a specific impedance method is used for defining the OOS protection settings. This paper innovates by testing the settings using the recordings of the major events of 15 September 2018 in two approaches: hybrid co-simulation and cyber-physical. Both tests have demonstrated the appropriate performance of the proposed settings and proving the proposed methodology works appropriately.

Comprehensive power swing detection by current signal modeling and prediction using the GMDH method

Power swing is an undesirable variation in power flow. This can be caused by large disturbances in demand load, switching, disconnection or reclosing lines. This phenomenon may enter the zones of distance relays and cause relay malfunction leading to the disconnection of healthy lines and undermining network reliability. Accordingly, this paper presents a new power swing detection method based on the prediction of current signal with a GMDH (Group Method of Data Handling) artificial neural network. The main advantage of the proposed method over its counterparts is the immunity to noise effect in signals. In addition, the proposed method can detect stable, unstable, and multi-mode power swings and is capable of distinguishing them from the variety of permanent faults occurring simultaneously. The method is tested for different types of power swings and simultaneous faults using DIgSILENT and MATLAB, and compared with some latest power swing detection methods. The results demonstrate the superiority of the proposed method in terms of response time, the ability to detect power swings of different varieties, and the ability to detect different faults that may occur simultaneously with power swings.