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Experimental validation of three nonlinear MPP Solar tracking techniques

机译：三种非线性MPP太阳能跟踪技术的实验验证

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— Solar Photovoltaic Systems are required to operate at the Maximum Power Point (MPP) for efficient operation. In this work, the performance of three Maximum Power Point Tracking (MPPT) techniques namely Incremental Conductance (InCond), Extremum Seeking Control (ESC) and Particle Swarm Optimization (PSO) are compared experimentally. The ACOPower 20 W PV panel and associated drives are first modeled in Simulink together with the respective controllers, and for experimental validation, an Arduino Mega microcontroller was used as a digital platform to implement the different algorithms. The strengths and shortcomings of the proposed algorithms, as well as important attributes, related to the accuracy and difficulty to implement the proposed algorithms are highlighted and discussed. It was found that all three algorithms were able to successfully track the MPP and their performances were as expected from simulated results.
机译：- 太阳能光伏系统需要在最大功率点（MPP）以进行高效操作。 在这项工作中，三个最大功率点跟踪（MPPT）技术的性能即增量电导（incond），极值寻求控制（ESC）和粒子群优化（PSO）进行了实验。 APOWOWER 20 W PV面板和相关的驱动器首先与相应的控制器一起建模，并且对于实验验证，Arduino Mega微控制器被用作实现不同算法的数字平台。 突出显示并讨论了与实现所提出的算法的准确性和难度相关的提出算法的优势和缺点，以及重要的属性。 结果发现，所有三种算法都能够成功跟踪MPP，并且它们的性能与模拟结果的预期一样。

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