Abstract
Power system stabilizers play an important role in reducing the low-frequency oscillation. In this article, the problem of robustly selecting the parameters of the power system stabilizers is studied. A new neural-like P systems optimization algorithm is proposed in order to optimize the power system stabilizer parameters. First, the structure of the neural-like P systems is established. Then, the operation rules, including forgetting rule, spiking rule, evolving rule, and transferring rule, are designed. Furthermore, a new objective function is constructed on the eigenvalues and damping ratio. Finally, the proposed algorithm is tested on the 16-machine and 68-bus system. The simulation results show the effectiveness and robustness of the proposed methods to select the optimal power system stabilizer parameters for damping out the low f oscillation.
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More From: Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering
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