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首页> 外文期刊>Scientific Research and Essays >Multi-machine power system stabilizer design using improved particle swarm optimization (PSO) with time-varying acceleration coefficients
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Multi-machine power system stabilizer design using improved particle swarm optimization (PSO) with time-varying acceleration coefficients

机译：多机动力系统稳定器设计，使用具有改进的时变加速度系数的粒子群算法（PSO）

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摘要

An efficient and most famous tool to enhance damping of the power system low frequency oscillations is the conventional widely used lead-lag Power System Stabilizer (PSS). To achieve the desired level of robust performance under transient situation, selecting a suitable design method for optimal tuning of PSS parameters is very important in multi-machine power system. Because, it is a multimodal and difficult combinatorial optimization problem, this paper presents a novel parameter automation strategy for Particle Swarm Optimization (PSO) called PSO with Time-Varying Acceleration Coefficients (PSO-TVAC). This optimization method has a strong ability to successfully control both global and local search in each iteration process for considerably increasing the probability of finding the global optimum solution. The PSO-TVAC algorithm is applied to optimal tuning PSS parameters problem in order to reduce the PSS design effort and find the best possible solution within a reasonable computation time. For this reason, the robustly selection of PSSs parameters is converted as an optimization problem based on the time domain-based objective function under different operating conditions. The robustness of the proposed method is demonstrated on a multi-machine power system in comparison with the classical PSO and conventional method based designed PSSs. It is shown through the nonlinear time domain simulation and some performance indices for a wide range of loading condition. The analysis of the results shows that the improved PSO-TVAC is not only very effective but also provides an excellent ability for damping low frequency oscillations and greatly enhance the dynamic stability of the power system. Moreover, the proposed PSO-TVAC algorithm is superior than that of the classical PSO one in terms of accuracy, convergence and computational effort.
机译：常规的超前滞后电力系统稳定器（PSS）是一种有效且最著名的工具，用于增强电力系统低频振荡的阻尼。为了在瞬态情况下达到所需的鲁棒性能水平，选择合适的设计方法来优化PSS参数的调整在多机电源系统中非常重要。因为这是一个多模式且困难的组合优化问题，所以本文提出了一种具有时变加速度系数（PSO-TVAC）的新型粒子群优化（PSO）参数自动化策略。这种优化方法具有在每次迭代过程中成功控制全局和局部搜索的强大能力，从而大大提高了找到全局最优解的可能性。 PSO-TVAC算法应用于优化PSS参数问题，以减少PSS设计工作并在合理的计算时间内找到最佳解决方案。因此，在不同的操作条件下，基于时域的目标函数将PSSs参数的鲁棒选择转换为优化问题。与经典PSO和基于传统方法的设计PSS相比，该方法在多机电源系统上的鲁棒性得到了证明。通过非线性时域仿真和在广泛负载条件下的一些性能指标可以看出这一点。结果分析表明，改进的PSO-TVAC不仅非常有效，而且还具有出色的衰减低频振荡的能力，并大大提高了电力系统的动态稳定性。此外，提出的PSO-TVAC算法在准确性，收敛性和计算工作量方面均优于经典PSO。

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