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Maximum Power Point Tracking in Solar Power Plants under Partially Shaded Condition

机译:部分遮蔽条件下太阳能发电厂的最大功率点跟踪

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摘要

efficiency of solar cells is the biggest when the controller adjusts the load according to the temperature of the solar cell and solar energy flux. This task is accomplished by various maximum power point tracking (MPPT) algorithms. This paper presents the analysis of maximum power point tracking efficiency, when some modules of the solar power plant are partially shaded. Mathematical models of photovoltaic module and Incremental Conduction (IncCond) algorithm are implemented in Matlab/Simulink environment. The simulation is performed using saved solar power flux signal, imitating real-world environmental conditions. This signal allows to compare different working modes of MPPT tracker and to calculate the efficiency of the algorithm. It is proposed to use artificial neural network (ANN) to increase the efficiency of (IncCond) algorithm. Using ANN allows faster maximum power point tracking.
机译:当控制器根据太阳能电池的温度和太阳能通量调整负载时,太阳能电池的效率最高。该任务通过各种最大功率点跟踪(MPPT)算法完成。本文介绍了当太阳能发电厂的某些模块部分阴影时最大功率点跟踪效率的分析。在Matlab / Simulink环境中实现了光伏模块的数学模型和增量电导(IncCond)算法。使用保存的太阳能通量信号进行仿真,以模拟现实环境条件。该信号允许比较MPPT跟踪器的不同工作模式,并计算算法的效率。为了提高(IncCond)算法的效率,建议使用人工神经网络(ANN)。使用ANN可以更快地跟踪最大功率点。

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