In our day, solar energy and wind energy are becoming more and more used as renewable sources by various countries for different uses such as in an isolated home. These energies admit a unique limitation related to the characteristic of energy instability. For this, the objective of this manuscript is to command and synchronize the power flow of a hybrid system using two sources of energy (solar and wind). The first contribution of our work is the utilization of an artificial neural network controller to command, at fixed atmospheric conditions, the maximum power point. The second contribution is the optimization of the system respecting real-time constraints to increase a generating system performance. As a matter of fact, the proposed system and the controller are modeled using MATLAB/Simulink and a Xilinx System Generator is utilized for hardware implementation. The simulation results, compared with other works in the literature, present high performance, efficiency, and precision. The suggested system and its control strategy give the opportunity of optimizing the hybrid power system performance, which is utilized in rural pumping or other smart house applications.

中文翻译：

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基于人工神经网络方法的混合风-太阳能发电系统的规模控制和硬件实现，用于抽水

在我们这个时代，太阳能和风能越来越多地被各国用作可再生能源，用于不同的用途，例如在一个孤立的家庭中。这些能量承认与能量不稳定性特征相关的独特限制。为此，本手稿的目的是使用两种能源（太阳能和风能）来控制和同步混合系统的功率流。我们工作的第一个贡献是利用人工神经网络控制器在固定的大气条件下控制最大功率点。第二个贡献是根据实时约束优化系统以提高发电系统性能。事实上，建议的系统和控制器使用 MATLAB/Simulink 建模，并使用 Xilinx 系统生成器进行硬件实现。与文献中的其他工作相比，仿真结果具有高性能、效率和精度。建议的系统及其控制策略为优化混合动力系统性能提供了机会，可用于农村抽水或其他智能家居应用。