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Optimal AGC tuning with genetic algorithms

机译:利用遗传算法优化AGC

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This paper deals with the application of genetic algorithms for optimizing the parameters of conventional automatic generation control (AGC) systems. A two-area nonreheat thermal system is considered to exemplify the optimum parameter search. A digital simulation is used in conjunction with the genetic algorithm optimization process. Several integral performance indices, or cost functions, are considered in the search for the optimal AGC parameters. The work is further extended to include the use of more elaborate feedback control strategies, such as the proportional-plus-integral type, within the decentralized frame. The results reported in this paper have not been obtained before and they demonstrate the effectiveness of the genetic algorithms in the tuning of the AGC parameters.
机译:本文讨论了遗传算法在优化常规自动发电控制(AGC)系统参数中的应用。考虑使用两区域非再热热系统来举例说明最佳参数搜索。将数字仿真与遗传算法优化过程结合使用。在寻找最佳AGC参数时会考虑几个整体性能指标或成本函数。这项工作进一步扩展到包括在分散框架内使用更精细的反馈控制策略,例如比例加积分类型。本文报道的结果以前尚未获得,它们证明了遗传算法在调整AGC参数方面的有效性。

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