Open AccessOptimal Shedding Against Voltage Collapse Based on Genetic Algorithm
Author(s) -
Mohamed Ali Zdiri,
Ahmed S. Alshammari,
Ahmed Alzamil,
Mohsen Ben Ammar,
Hsan Hadj Abdallah
Publication year - 2021
Publication title -
engineering, technology and applied science research/engineering, technology and applied science research
Language(s) - English
Resource type - Journals
eISSN - 2241-4487
pISSN - 1792-8036
DOI - 10.48084/etasr.4448
Subject(s) - load shedding , computer science , electric power system , voltage , reliability engineering , context (archaeology) , limit (mathematics) , rendering (computer graphics) , electricity , mathematical optimization , control theory (sociology) , power (physics) , engineering , electrical engineering , mathematics , artificial intelligence , paleontology , mathematical analysis , physics , control (management) , quantum mechanics , biology
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.