基于滞后电流控制逆变器的光伏系统神经网络MPPT控制方案

R. Dubey
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引用次数: 17

摘要

目前光伏板是可再生能源的主要来源之一。该面板提供直流电源,可直接用于直流电源应用。在我们的日常生活中,我们通常使用交流负载。因此,本文提出了一种鲁棒性强且易于实现的逆变器。提出了一种固定频带的迟滞电流控制逆变器,在输出电流THD小于5%的条件下确定负载变化值。逆变器的开发采用三级技术。通过构建人工神经网络对面板功率进行最大功率跟踪。系统性能是根据MPPT控制器的效率和逆变器在独立负载下运行的灵活性来衡量的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural network MPPT control scheme with hysteresis current controlled inverter for photovoltaic system
These days photovoltaic panel are the one of the main source of renewable power. This panel gives the dc power which can be directly used in dc power application. In our daily life we generally work with ac load. Hence an inverter is proposed in this paper which will provide a robust operation and very simple to implement. A hysteresis current controlled inverter is proposed with fixed band and the value of the load variation is determined with output current THD lower than 5%. Inverter is developed with three level techniques. Maximum power tracking of panel power is done by constructing artificial neural network. System performance is measured in terms of the efficiency of the MPPT controller and flexibility in the inverter operation for standalone load.
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