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

Yosra Welhazi, T. Guesmi, H. H. Abdallah
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引用次数: 8

Abstract

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.
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基于多目标粒子群算法的多机电力系统特征值分配
将多目标粒子群优化算法应用于多机电力系统稳定器的多目标设计。该方法基于MOPSO算法搜索PSS在各种工况下的最优参数设置。在此基础上,提出了模糊集理论来提取最优妥协解。利用MOPSO选择稳定器,将轻阻尼和无阻尼机电模式转移到s平面的指定区域。将稳定器参数的整定问题转化为基于特征值的多目标函数优化问题。以三机九总线系统为例,研究了该方法在不同运行条件下的性能。通过特征值分析、非线性仿真结果和大范围加载条件下的一些性能指标,验证了该方法在阻尼机电模态和大幅度提高动力稳定性方面的有效性。
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