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Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems
Abstract
Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality, heuristics-based swarm intelligence can be an efficient alternative. Particle swarm optimization (PSO), part of the swarm intelligence family, is known to effectively solve large-scale nonlinear optimization problems. This paper presents a detailed overview of the basic concepts of PSO and its variants. Also, it provides a comprehensive survey on the power system applications that have benefited from the powerful nature of PSO as an optimization technique. For each application, technical details that are required for applying PSO, such as its type, particle formulation (solution representation), and the most efficient fitness functions are also discussed.
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Cites
A new optimizer using particle swarm theory
Eberhart, R., & Kennedy, J. (2002) · MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science · doi:10.1109/mhs.1995.494215 · Cited by 16,067
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Particle swarm optimization algorithm: An overview
Wang, D., Tan, D., & Liu, L. (2018) · Soft Computing · doi:10.1007/s00500-016-2474-6 · Cited by 3,343
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Philip Chen, C. L., & Zhang, C.-Y. (2014) · Information Sciences · doi:10.1016/j.ins.2014.01.015 · Cited by 3,047
A comparative study of equivalent circuit models for Li-ion batteries
Hu, X., Li, S., & Peng, H. (2012) · Journal of Power Sources · doi:10.1016/j.jpowsour.2011.10.013 · Cited by 2,179
Seeker Optimization Algorithm for Optimal Reactive Power Dispatch
Dai, C., Chen, W., Zhu, Y., & Zhang, X. (2009) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2009.2021226 · Cited by 448
Metadata
- Authors
- del Valle, Y., Venayagamoorthy, G. K., Mohagheghi, S., Hernandez, J.-C., & Harley, R. G.
- Venue
- IEEE Transactions on Evolutionary Computation
- Published
- 2008-04
- Volume
- 12
- Issue
- 2
- Pages
- 171-195
- ISSN
- 1089-778X (ISSN-L)
- 1941-0026
- OpenAlex
- W2168747298
- Cited by
- 2,277
- References
- 1
- FWCI
- 182.33
- Type
- journal article
- Language
- en
- Open access
- closed
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- del Valle, Y., Venayagamoorthy, G. K., Mohagheghi, S., Hernandez, J.-C., & Harley, R. G. (2008). Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems. IEEE Transactions on Evolutionary Computation. https://doi.org/10.1109/tevc.2007.896686
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