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An Analytical Review of PSO Algorithm Applications in Power System Flexibility and Resilience
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Mohanad Faisal Abed Al-Safi1   , Afshin Lashkarara *2 , Hajar Bagheri Tolabi3 |
1- Department of Electrical Engineering, SR.C., Islamic Azad University, Tehran, Iran
2- Department of Electrical Engineering, Dez.C., Islamic Azad University, Dezful, Iran , Lashkarara@iau.ac.ir
3- Department of Electrical Engineering, Khor.C., Islamic Azad University, Khorramabad, Iran |
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Abstract: (64 Views) |
The fundamental transformation of the power system in recent years, with the development of the penetration of renewable energy sources, microgrids and the spread of emerging loads such as electric vehicles, has created new challenges in the reliable and sustainable operation of the power system. Contrary to the significant environmental and economic benefits that these changes have brought, they have increased the level of uncertainty and fluctuations in operation. In such circumstances, the concepts of "flexibility" and "resilience" have been proposed as two key indicators of the performance of power systems. Flexibility refers to the ability of the system to quickly adapt to changes in normal operating conditions, while resilience focuses on the capacity of the system to withstand severe disturbances, reduce performance degradation and recover quickly after crises. The complexity of the issues related to these two concepts has caused the use of classical optimization methods to face limitations and has attracted the attention of researchers to meta-heuristic algorithms. Particle Swarm Optimization (PSO) algorithm has gained a special place in power systems due to its simple structure, adaptive capabilities, and good performance in nonlinear and multi-objective problems. This article, with a review and analytical approach, comprehensively examines the application of PSO algorithm in increasing the flexibility and resilience of power systems. By analyzing 40 selected articles, first, basic concepts are recalled, then the role of PSO in flexible resource management and improving network resilience is analyzed. In the following, research gaps are identified and future research directions are suggested. |
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| Keywords: Particle Swarm Optimization (PSO), Power System Flexibility, Power System Resilience, Demand Response, Metaheuristic Optimization, Microgrid, Uncertainty Modeling. |
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Full-Text [PDF 1012 kb]
(29 Downloads)
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Type of Study: Review article |
Subject:
Special
Received: 2025/06/13 | Accepted: 2025/08/27 | Published: 2025/09/1
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