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Design of intelligent Maximum Power Point Tracking (MPPT) technique based on swarm intelligence based algorithms

机译:基于群体智能算法的智能最大功率点跟踪(MPPT)技术设计

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摘要

Main objective of this paper is to develop an intelligent and efficient Maximum Power Point Tracking (MPPT) technique. Two most recently introduced and popular swarm intelligent based algorithms: Firefly algorithm (FA) and Artificial Bee Colony (ABC) has been used in this study to develop a novel technique to track the Maximum Power Point (MPP) of a solar cell module. The performances of two algorithms in this context have been compared with other popular evolutionary computing techniques like PSO, DE and GA. Simulations were done in MATLAB/SIMULINK environment and simulation results show that proposed approach can obtain MPP to a good precision under different solar irradiance and environmental temperatures.
机译:本文的主要目的是开发一种智能,高效的最大功率点跟踪(MPPT)技术。这项研究中使用了两种最新推出且最受欢迎的基于群体智能的算法:萤火虫算法(FA)和人工蜂群(ABC),以开发一种跟踪太阳能电池模块最大功率点(MPP)的新技术。在这种情况下,两种算法的性能已与其他流行的进化计算技术(如PSO,DE和GA)进行了比较。在MATLAB / SIMULINK环境下进行了仿真,仿真结果表明,该方法在不同太阳辐照度和环境温度下都能获得较高的精度。

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