首页> 外文会议>2016 IEEE International Conference on Power and Renewable Energy >A hybrid Fuzzy Logic Controller-Firefly Algorithm (FLC-FA) based for MPPT Photovoltaic (PV) system in solar car
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A hybrid Fuzzy Logic Controller-Firefly Algorithm (FLC-FA) based for MPPT Photovoltaic (PV) system in solar car

机译:基于MPPT光伏系统的混合模糊逻辑控制器-萤火虫算法(FLC-FA)

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摘要

This paper propose Firefly Algorithm (FA) new method for tuning the membership function of fuzzy logic controller for Maximum Power Point Tracker (MPPT) system Photovoltaic solar car, that consist of hybrid Fuzzy Logic Controller - Firefly Algorithm (FLC-FA) for the parameter. There are many MPPT methods for photovoltaic (PV) system, Perturbation and Observation (PnO), fuzzy logic controller (FLC) standard, and hybrid Fuzzy logic controller firefly algorithm (FLC-FA) is compared in this paper. The proposed FLC-FA algorithm is to obtain the optimal solution for MPPT for photovoltaic (PV) systems for solar cars. The result Fuzzy logic controller firefly (FLC-FA) of the proposed method, the highest maximum strength and efficiency generated is PnO = 96.31%, Standard FLC = 99.88% and Proposed FLC-FA = 99.98%. better than PnO and Fuzzy logic controller standard method. The main advantage of the proposed FLC-FA is more efficient and accurate than the still fuzzy logic controller standard.
机译:本文提出了一种Firefly算法(FA)用于调节最大功率点跟踪器(MPPT)系统光伏太阳能汽车模糊控制器隶属函数的新方法,该方法由混合模糊逻辑控制器-Firefly算法(FLC-FA)组成。 。本文比较了光伏系统(PV)的MPPT方法,摄动与观测(PnO),模糊逻辑控制器(FLC)标准以及混合模糊逻辑控制器萤火虫算法(FLC-FA)。提出的FLC-FA算法旨在为太阳能汽车的光伏(PV)系统获得MPPT的最佳解决方案。所提出方法的结果模糊逻辑控制器萤火虫(FLC-FA),产生的最大最大强度和效率为PnO = 96.31%,标准FLC = 99.88%和拟议FLC-FA = 99.98%。优于PnO和模糊逻辑控制器标准方法。所提出的FLC-FA的主要优点是比仍然模糊的逻辑控制器标准更为有效和准确。

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