Abstract
The increasing complexity of today's applications has surfaced the importance of meta-heuristic techniques which can deal with multi-variable, multi-constraints, highly non-linear and non-smooth problems. Their superior performance and immunity of getting trapped in local maxima or minima made them eminent when compared with classical optimization methods, which have several limitations. In this context, implementation and evaluation of Grey Wolf optimization Algorithm (GWOA) on power system stability enhancement will be carried. The objective function is to maximize the minimum damping ratio of the controller to enhance stability and ensure faster damping. The results will be then compared with other evolutionary techniques, particularly Real-coded Genetic Algorithm (RCGA) and Differential Evolution (DE) method. The simulation results will be established using MATLAB.
| Original language | English |
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| Title of host publication | 2019 IEEE 10th GCC Conference and Exhibition, GCC 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538694770 |
| DOIs | |
| State | Published - Apr 2019 |
Publication series
| Name | 2019 IEEE 10th GCC Conference and Exhibition, GCC 2019 |
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Bibliographical note
Publisher Copyright:© 2019 IEEE.
Keywords
- Constrained optimization
- Differential evolution method
- Evolutionary algorithm
- Grey wolf optimization
- Meta-heuristic techniques
- Natureinspired optimization
- Real-coded genetic algorithm
ASJC Scopus subject areas
- Information Systems and Management
- Biomedical Engineering
- Energy Engineering and Power Technology
- Renewable Energy, Sustainability and the Environment
- Safety, Risk, Reliability and Quality
- Instrumentation
- Artificial Intelligence
- Computer Networks and Communications