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The Energy Saving Technology of a Photovoltaic System's Control on the Basis of the Fuzzy Selective Neuronet

机译:基于模糊选择性神经网络的光伏系统控制节能技术

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This paper presents the energy saving technology of a photovoltaic system's control. Based on the photovoltaic system's state, the fuzzy selective neural net creates an effective control signal under random perturbations. The architecture of the selective neural net was evolved using a neuro-evolutionary approach. The validity and advantages of the proposed energy saving technology of a photovoltaic system's control are demonstrated using numerical simulations. The simulation results show that the proposed technology achieves real-time control speed and competitive performance, as compared to a classical control scheme with a PID controller.
机译:本文介绍了光伏系统控制的节能技术。基于光伏系统的状态,模糊选择性神经网络会在随机扰动下创建有效的控制信号。选择性神经网络的体系结构是使用神经进化方法进化的。通过数值模拟证明了所提出的光伏系统控制节能技术的有效性和优势。仿真结果表明,与经典的带有PID控制器的控制方案相比,该技术实现了实时控制速度和竞争性能。

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