基于神经网络与模糊控制的光伏MPPT复合控制的研究-控制工程专业论文.docx

I I 摘要 随着全球经济的持续快速发展，大量传统化石燃料被消耗，煤炭、石油、天 然气等能源的储量急剧下降，能源危机显现。在这种背景下，太阳能作为一种新 兴的绿色可再生能源受到各国的青睐。尤其是近几十年，由于经济的快速发展， 光伏产业也得到了前所未有的发展。但是，由于太阳能电池成本高、转化效率低 等缺点严重阻碍了光伏产业的进一步发展。为此，各国对于采用最大功率跟踪的 方法提高太阳能电池的转化效率做了大量研究。所以，本文研究的重点就是使太 阳能电池工作在最大工作点，从而得到最大输出功率。 首先，本文利用 MATLAB/Simulink 建立了 BOOST 转换电路以及光伏电池 的仿真模型，并对光伏电池所表现出的伏安特性做了详细的分析。其次，文章对 目前常用的几种最大功率跟踪方法进行了对比分析，并给出了一些简单的改进措 施。然后，本文基于 BP 神经网络建立了最大功率点电压预测模型，并进行了仿 真实验，实验结果显示利用神经网络能够快速准确的预测最大功率点电压。 最后，文章对于常用方法存在的问题，提出了神经网络与模糊控制相结合的 光伏 MPPT 控制方法，并建立了仿真模型。仿真结果表明，该方法能够很好的 避免传统方法存在的功率振荡和误判问题，并且系统反应速度快、精度较高。 关键词： 太阳能电池，最大功率跟踪，MATLAB/Simulink 仿真，神经网络，模 糊控制 I II Abstract With the rapid development of global economy, a large number of traditional fossil fuel consumption, coal, oil, natural gas and other energy reserves fell sharply, the energy crisis appeared. In this context, the solar energy as a new kind of green renewable energy was favored by all. Especially in recent years, due to the rapid economic development, the photovoltaic industry has been hitherto unknown development. However, due to the high cost of solar cell conversion efficiency is low, seriously hindered the further development of photovoltaic industry. Therefore, the method of maximum power point tracking to improve the conversion efficiency of solar cells made a lot of research. Therefore, the focus of this paper is to make solar cells work at the maximum point, so as to obtain the maximum output power. Firstly, the simulation model of MATLAB/Simulink established the BOOST conversion circuit and photovoltaic cells, photovoltaic current-voltage characteristics and performance were analyzed in detail. Secondly, this paper analyzes the current several commonly used maximum power tracking method, and gives some simple measures of improvement. Then, the BP neural network was established based on the maximum power point voltage prediction model and the simulation experiments, the experimental results showed that can predict the maximum power voltage quickly and accurat