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Proposal of an Adaptive Neurofuzzy System to Control Flow Power in Distributed Generation Systems

机译:用于控制分布式发电系统流量的自适应神经舒张系统的提议

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Systems of distributed generation have shown to be a remarkable alternative to a rational use of energy. Nevertheless, the proper functioning of them still manifests a range of challenges, including both the adequate energy dispatch depending on the variability of consumption and the interaction between generators. This paper describes the implementation of an adaptive neurofuzzy system for voltage control, regarding the changes observed in the consumption within the distribution system. The proposed design employs two neurofuzzy systems, one for the plant dynamics identification and the other for control purposes. This focus optimizes the controller using the model achieved through the identification of the plant, whose changes are produced by charge variation; consequently, this process is adaptively performed. The results show the performance of the adaptive neurofuzzy system via statistical analysis.
机译:分布式发电系统已显示是对合理使用能量的显着替代品。尽管如此,它们的正常运作仍然表现出一系列挑战,包括根据消耗的可变性和发电机之间的相互作用的充分能源调度。本文介绍了用于电压控制的自适应神经舒张系统的实现,关于在分配系统内的消耗中观察到的变化。该设计采用两个神经繁茂的系统,一个用于植物动力学识别,另一个用于控制目的。该重点使用通过识别工厂的模型来优化控制器,其变化由充电变化产生;因此,自适应地执行该过程。结果显示了通过统计分析的自适应神经舒张系统的性能。

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