Sharif University of Technology Scientia Iranica 1026-3098 28 Special issue on collective behavior of nonlinear dynamical networks 2021 06 01 Generation rejection scheme based on a combinational rotor angle trajectory prediction 1579 1591 21690 10.24200/sci.2019.54136.3611 EN A. A. Hajnorouzi Centre of Excellence for Power System Automation and Operation, Iran University of Science and Technology, Tehran, Iran F. Aminifar School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran H. A. Shayanfar Centre of Excellence for Power System Automation and Operation, Iran University of Science and Technology, Tehran, Iran Journal Article 2019 07 29 This paper presents a response-based generating rejection scheme (GRS) based on an angular stability prediction logic to initiate the outage of accelerated generating units while saving the rest of generating units from the loss of synchronism. First trigonometric, polynomial, and hybrid models of rotor angle trajectory based on the reasonable assumptions are proofed. Then, by taking these models in the prediction step, through the maximum use of measured data based on defining the forecast horizon (FH) and data window with incremental length, the stability/instability of generating units is separately predicted. Next, the status of tripping signal based on a combinational logic of the output results of the angular stability prediction method is specified. In the developed logic, if at least two models of the three designated models yield the same response about the unit stability status, the trip signal is accordingly fired or blocked. The proposed method is examined on the one machine infinite bus and the WSCC standard test bed under different operation and fault scenarios. The obtained results demonstrate that beside simplicity, low computational burden, and very short processing time, the proposed combinatorial method outperforms the existing ones working with individual prediction models. https://scientiairanica.sharif.edu/article_21690_649e7bd4fa544f1d97cc28aeab64cdc5.pdf