Optimal Shedding Against Voltage Collapse Based on Genetic Algorithm


  • M. A. Zdiri CEM Laboratory, Engineering School of Sfax, Tunisia
  • A. S. Alshammari Department of Electrical Engineering, University of Hail, Saudi Arabia
  • A. A. Alzamil Electrical Engineering Department, College of Engineering, University of Hail, Saudi Arabia
  • M. Ben Ammar CEM Laboratory, Engineering School of Sfax, Tunisia
  • H. H. Abdallah CEM Laboratory, Engineering School of Sfax, Tunisia
Volume: 11 | Issue: 5 | Pages: 7695-7701 | October 2021 | https://doi.org/10.48084/etasr.4448


The prevalent tendency in power transmission systems is to operate closer and closer to the energy limit, rendering system voltage instability a commonly widespread phenomenon. It is, therefore, necessary that certain remedial corrective controls need be undertaken whenever these systems tend towards failure. In this respect, load shedding stands as a major correction mechanism and such a failure can be prevented and nominal system voltage can be resumed. It is worth noting however that load shedding must be implemented very carefully to ensure the satisfaction of both the customer and the electricity-production company. In this context, our focus of interest is laid on load and machine shedding against voltage collapse as an effective corrective method. It is important to note that such a problem turns out to be commonly defined as an optimization problem under constraints. Using genetic algorithms as resolution methods, the application of the proposed methods was implemented on the 14-node IEEE test network, while considering a number of different case studies.


power transmission, load and machine shedding, voltage collapse, genetic algorithms, 14-node IEEE test network


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How to Cite

M. A. Zdiri, A. S. Alshammari, A. A. Alzamil, M. Ben Ammar, and H. H. Abdallah, “Optimal Shedding Against Voltage Collapse Based on Genetic Algorithm”, Eng. Technol. Appl. Sci. Res., vol. 11, no. 5, pp. 7695–7701, Oct. 2021.


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