MPPT方法在提高光伏系统性能中的应用

N. Boutasseta, M. Bouakkaz, I. Attoui, Nadir Fergani, A. Bouraiou, NECAIBIA Ammar
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引用次数: 2

摘要

太阳能是可再生能源发电的主要来源。利用最大功率点跟踪技术设计了一种高效的光伏太阳能转换系统。最初,考虑了光伏系统性能的规划和估计方面。光伏阵列的最佳工作点被称为最大功率点(MPP),它根据电池温度和太阳的绝缘水平而变化。为了实现最大功率点跟踪(MPPT)的目标,本文开发了三种算法。第一种算法基于神经网络方法(ANN),使用反向传播作为其训练算法。第二种算法基于模糊逻辑(FL),它利用面板的属性进行最大功率点预测,其中性能取决于模糊规则的逻辑。第三种方法是基于Hill climb (HC)算法,通过将功率变化与控制变量的变化相关联来确定最大功率点,该方法具有系统与网络无关的优点,不需要进行周期调谐。
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Implementation of MPPT Methods for improving the Performance of Photovoltaic Systems
Solar energy represents the main source of renewable power generation. This paper deals with the design of an efficient photovoltaic (PV) solar energy conversion system using maximum power point tracking techniques. Initially, aspects of planning and estimation of the PV systems performance were considered. The optimum operating point of a photovoltaic array is called Maximum Power Point (MPP), which varies depending on the cell temperature and the sun's insulation level. In order to achieve the goal of the Maximum Power Point Tracking (MPPT), three types of algorithms were developed in this work. The first algorithm is based on a neural network approach (ANN) that uses the backpropagation as its training algorithm. The second algorithm is based on fuzzy logic (FL), which uses the properties of the panel for its Maximum Power Point prediction, where the performance depends on the logic of the fuzzy rule. The third method is based on the Hill climbing (HC) algorithm that determines the maximum power point by correlating the changes in power with the changes in the control variable which has the advantage of network independent system and periodic tuning is not required.
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