首页> 外文期刊>Renewable Power Generation, IET >Efficient maximum power point tracking using model predictive control for photovoltaic systems under dynamic weather condition
【24h】

Efficient maximum power point tracking using model predictive control for photovoltaic systems under dynamic weather condition

机译:使用模型预测控制在动态天气条件下对光伏系统进行有效的最大功率点跟踪

获取原文
获取原文并翻译 | 示例
       

摘要

This study presents a high-efficient maximum power point tracking (MPPT) of photovoltaic (PV) systems by means of model-predictive control (MPC) techniques that is applied to a high-gain DC-DC converter. The high variability and stochastic nature of solar energy requires that the MPPT control continuously adjust the power converter operating point in order to track the changing maximum power point; a concept well known in the literature. The main contribution of this study is a model-predictive-based controller with a fixed step that is combined with the traditional incremental conductance (INC) method. This technique improves the speed at which the controller can track rapid changes in solar insolation and results in an increase in the overall efficiency of the PV system. The controller speeds up convergence since MPC predicts error before the switching signal is applied to the high-gain multilevel DC-DC converter and thus is able to choose the next switch event to minimise error between the commanded and actual converter operation. Comparing the proposed technique to the conventional INC method shows substantial improvement in MPPT effectiveness and PV system performance. The performance of the proposed MPC-MPPT is analysed and validated experimentally.
机译:这项研究通过模型预测控制(MPC)技术提出了一种光伏(PV)系统的高效最大功率点跟踪(MPPT),该技术已应用于高增益DC-DC转换器。太阳能的高度可变性和随机性要求MPPT控制不断调整功率转换器的工作点,以便跟踪变化的最大功率点。文学中众所周知的概念。这项研究的主要贡献是具有固定步长的模型预测控制器,该控制器与传统增量电导(INC)方法相结合。该技术提高了控制器跟踪太阳直射的快速变化的速度,并提高了光伏系统的整体效率。由于MPC在将开关信号施加到高增益多电平DC-DC转换器之前就预测了错误,因此该控制器加快了收敛速度,因此能够选择下一个开关事件,以最大程度地减小命令和实际转换器操作之间的误差。将提出的技术与常规INC方法进行比较,显示出MPPT有效性和PV系统性能的显着提高。提出的MPC-MPPT的性能经过实验分析和验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号