PSS参数的粒子群优化及其在DIgSILENT PowerFactory中的应用

2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE) Pub Date : 2023-05-12 DOI:10.1109/CEEPE58418.2023.10165758

Yonghan Liu, Jing He, Peng Wang, Haoran Zhao

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引用次数: 0

摘要

电网日趋复杂，低频振荡频发，对电力系统的安全稳定运行提出了重大挑战。电力系统稳定器通常通过改善阻尼和抑制低频振荡来增强系统的稳定性。然而，优化PSS参数是一项具有挑战性的任务，通常需要大量的分析或现场实验。为了解决这一挑战，本研究利用DIgSILENT PowerFactory软件和粒子群优化算法，提出了一种有效的pss参数优化方法。在39节点系统上进行了验证，结果表明该方法改善了系统的阻尼，提高了系统的稳定性。该方法为寻求优化电力系统PSS参数的工程师提供了一种易于实现的解决方案。

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Particle Swarm Optimization for PSS Parameters and Application to DIgSILENT PowerFactory

The power grid becomes complex, low-frequency oscillations occur more frequently, posing significant challenges to power systems' safe and stable operation. Power system stabilizers are commonly used to enhance system stability by improving damping and suppressing low-frequency oscillations. However, optimizing PSS parameters is a challenging task that typically requires extensive analysis or on-site experimentation. To address this challenge, this study proposes an efficient parameter optimization method for PSSs using the DIgSILENT PowerFactory software and the particle swarm optimization algorithm. The proposed method is validated on a 39-node system, and the results show that the proposed method improves system damping and enhances stability. This method offers an easy-to-implement solution for engineers seeking to optimize PSS parameters in power systems.

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来源期刊

2023 6th International Conference on Energy, Electrical and Power Engineering (CEEPE)

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