This paper discusses the effect of multi-objective function in angle stability improvement for a single machine connected to an infinite bus system (SMIB). Minimum damping ratio, ξmin and maximum damping factor, σmax which are commonly used to indicate oscillatory stability condition in power system are merge in certain ratio to produce a multi-objective function, FMO. This new index brings the advantages of the two indices without compromising the weakness of the index involved. In this study, FMO is applied to tune parameters of static var compensator with proportional-integral-derivative controller (SVC-PID) to improve damping efficiency in SMIB. The result is compared with a system connected to power system stabilizer attached with lead lag controller (PSS-LL). The parameters of SVC-PID and PSS-LL are optimized by particle swarm optimization method. Validation based on speed response, phase plane and determination of eigenvalues confirms that the proposed FMO is more effective for solving angle stability problems compared to single objective function.

中文翻译：

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用于改善 PSS 和基于 SVC 的 SMIB 的角度稳定性的群智能方法

本文讨论了多目标函数对连接到无限总线系统 (SMIB) 的单机的角度稳定性改进的影响。将常用来表示电力系统振荡稳定条件的最小阻尼比 ξmin 和最大阻尼因数 σmax 按一定比例合并，得到一个多目标函数 FMO。这个新指数在不损害所涉及指数的弱点的情况下，带来了两个指数的优势。在这项研究中，FMO 被应用于调整带有比例积分微分控制器 (SVC-PID) 的静态无功补偿器的参数，以提高 SMIB 的阻尼效率。结果与连接到带有超前滞后控制器 (PSS-LL) 的电力系统稳定器的系统进行了比较。SVC-PID和PSS-LL的参数采用粒子群优化方法进行优化。基于速度响应、相平面和特征值确定的验证证实，与单一目标函数相比，所提出的 FMO 在解决角度稳定性问题方面更有效。