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Eigenvalue Assignments in Multimachine Power Systems Using Multi-Objective PSO Algorithm

机译:使用多目标PSO算法的多机电力系统特征值分配

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摘要

Applying multi-objective particle swarm optimization (MOPSO) algorithm to multi-objective design of multimachine power system stabilizers (PSSs) is presented in this paper. The proposed approach is based on MOPSO algorithm to search for optimal parameter settings of PSS for a wide range of operating conditions. Moreover, a fuzzy set theory is developed to extract the best compromise solution. The stabilizers are selected using MOPSO to shift the lightly damped and undamped electromechanical modes to a prescribed zone in the s-plane. The problem of tuning the stabilizer parameters is converted to an optimization problem with eigenvalue-based multi-objective function. The performance of the proposed approach is investigated for a three-machine nine-bus system under different operating conditions. The effectiveness of the proposed approach in damping the electromechanical modes and enhancing greatly the dynamic stability is confirmed through eigenvalue analysis, nonlinear simulation results and some performance indices over a wide range of loading conditions.
机译:提出了将多目标粒子群算法(MOPSO)应用于多机电力系统稳定器(PSS)的多目标设计。所提出的方法基于MOPSO算法,以在广泛的工作条件下搜索PSS的最佳参数设置。此外,发展了模糊集理论以提取最佳折衷解决方案。使用MOPSO选择稳定器,以将轻微阻尼和未阻尼的机电模式转移到s平面中的指定区域。使用基于特征值的多目标函数将调整稳定器参数的问题转换为优化问题。在不同的运行条件下,针对三机九总线系统研究了该方法的性能。通过特征值分析,非线性仿真结果以及在较宽的载荷条件下的一些性能指标,证实了该方法在阻尼机电模式和大大提高动态稳定性方面的有效性。

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