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The Research of Voltage Prediction of Solar UAV Panel by Improved Mind Evolutionary Algorithm

机译:改进思想进化算法在太阳能无人机面板电压预测中的研究

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Solar energy is a new energy, which is not only perennial but also obtainable to every strata of the world. The use of solar photovoltaic systems (SPV) is the process of converting solar energy into electricity. Photovoltaic modules are mounted on the wings of solar unmanned aerial vehicles. In this paper, a new MPPT controller is proposed to predict the voltage to obtain the maximum power from the solar panel. The proposed MPPT controller is based on mind evolution algorithm (MEA) optimized back propagation neural network (BPNN). Firstly, the mind evolution algorithm model is constructed based on topology of BP Neural Network. Then, it is used to obtain the optimal solutions, which is regarded as initial weights and threshold value of BP Neural Network. Finally, the simulation experiment is carried out by using MATLAB software. The prediction results of the BP neural network optimized by the mind evolution algorithm are compared.
机译:太阳能是一种新能源,它不仅是多年生的,而且也是世界上所有阶层均可获得的。太阳能光伏系统(SPV)的使用是将太阳能转化为电能的过程。光伏模块安装在太阳能无人机的机翼上。在本文中,提出了一种新的MPPT控制器来预测电压以从太阳能电池板获得最大功率。所提出的MPPT控制器基于思维进化算法(MEA)优化的反向传播神经网络(BPNN)。首先,基于BP神经网络的拓扑结构构建思想进化算法模型。然后,将其用于获取最优解,该最优解被视为BP神经网络的初始权重和阈值。最后,利用MATLAB软件进行了仿真实验。比较了用思维进化算法优化的BP神经网络的预测结果。

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