Fuzzy logic approach based mppt for the dynamic performance improvement for PV systems

2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B) Pub Date : 2017-10-01 DOI:10.1109/ICEE-B.2017.8191986

N. Aouchiche, M. S. A. Cheikh, M. Becherif, M. Ebrahim, A. Hadjarab

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引用次数: 8

Abstract

Renewable Energies (RE) are considered as an important alternative sources of energy for the generation of electricity such as hydrogen and photovoltaic energies. To ensure an efficient photovoltaic energy conversion several Maximum Power Point Tracking (MPPT) algorithms have been developed to incite the PV field to deliver maximum power. This paper presents a comprehensive comparative study of two classical MPPT algorithms against the Artificial Intelligence (AI)-based one under hypothetical and realistic atmospheric conditions. The suggested algorithms are Perturb and Observe (P&O) algorithm, Incremental of Conductance (IC) algorithm and Fuzzy Logic based Incremental Conductance (FL-IC). After the PV verification under hypothetical conditions such as slow and fast irradiance variations, the effectiveness of those numerous methods are evaluated in terms of stability, robustness and rapidity considering one-year realistic atmospheric irradiance data for Bouzareah region. Through MatlabTM-simulation results, the superiority of the FL-IC over other both classical algorithms is highlighted.

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基于模糊逻辑方法的光伏系统动态性能优化

可再生能源(RE)被认为是发电的重要替代能源，如氢和光伏能源。为了保证高效的光伏能量转换，开发了几种最大功率点跟踪(MPPT)算法来激励光伏场输出最大功率。本文在假设和现实大气条件下，对两种经典MPPT算法与基于人工智能(AI)的MPPT算法进行了全面的比较研究。提出的算法有摄动和观察(P&O)算法、电导增量(IC)算法和基于模糊逻辑的电导增量(FL-IC)算法。在假设条件下(如辐照度变化缓慢和快速)进行PV验证后，考虑Bouzareah地区一年的实际大气辐照度数据，从稳定性、鲁棒性和快速性方面评估了多种方法的有效性。通过matlabtm仿真结果，突出了FL-IC相对于其他两种经典算法的优越性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B)

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