法属圭亚那光伏电池微电网系统中控制电池电流的人工神经网络:提高电池寿命

Chabakata Mahamat, Gustave Ilunga, Jessica Bechet, Sara Zermani, L. Linguet
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引用次数: 0

摘要

本文提出了一种应用于法属圭亚那独立微电网控制的人工神经网络。该微电网由光伏(PV)源和电池存储组成,以提供直流负载。本文测试了与Levenberg-Marquardt算法相关联的神经网络的不同配置,以选择最佳配置来优化系统的控制。然后,我们重点讨论了与传统的比例积分控制(PI控制)相比,使用这种类型的控制的优势。最后,给出并讨论了用Matlab Simulink软件进行的仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Neural Network in Photovoltaic-Battery Microgrid System for Controlling the Battery Current in French Guiana : Battery Life Improvement
This paper presents an artificial neural network applied to control a standalone microgrid in French Guiana. This microgrid is composed of a Photovoltaic (PV) source and a battery storage to supply a DC load. In this paper, different configurations of neural network associated with the Levenberg-Marquardt algorithm are tested to choose the best configuration to optimize the control of our system. Then, we focus on the advantage of using this type of control compared to the conventional proportional integral control (PI control). Finally, we present and discuss the results of our simulation obtained with Matlab Simulink software.
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