Scaled Conjugate Gradient Artificial Neural Network-Based Ripple Current Correlation MPPT Algorithms for PV System

IF 2.1 4区 工程技术 Q3 CHEMISTRY, PHYSICAL
Abdullah M. Noman, Hamed Khan, H. A. Sher, Sulaiman Z. Almutairi, Mohammed H. Alqahtani, Ali S. Aljumah
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引用次数: 2

Abstract

This article proposes a hybrid scheme of maximum power point tracking (MPPT) based on artificial neural network (ANN) and ripple current correlation (RCC). ANN model is established using the data generated through RCC MPPT. Scaled conjugate gradient ANN is applied to gauge the performance improvement. The proposed scheme is validated through simulations. For this, the proposed system is applied to three different environmental scenarios which are standard testing condition of a PV module, under variable irradiance condition, and variable temperature condition. It is established that the proposed system is well capable of tracking the maximum power point under various test conditions.
基于比例共轭梯度人工神经网络的光伏系统纹波电流相关MPPT算法
提出了一种基于人工神经网络(ANN)和纹波电流相关(RCC)的最大功率点跟踪混合方案。利用RCC MPPT生成的数据建立了人工神经网络模型。采用缩放共轭梯度人工神经网络来衡量性能的提高。通过仿真验证了该方案的有效性。为此,提出的系统应用于三种不同的环境场景,分别是光伏组件的标准测试条件、变辐照度条件和变温度条件。结果表明,该系统在各种测试条件下都能很好地跟踪最大功率点。
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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来源期刊
CiteScore
6.00
自引率
3.10%
发文量
128
审稿时长
3.6 months
期刊介绍: International Journal of Photoenergy is a peer-reviewed, open access journal that publishes original research articles as well as review articles in all areas of photoenergy. The journal consolidates research activities in photochemistry and solar energy utilization into a single and unique forum for discussing and sharing knowledge. The journal covers the following topics and applications: - Photocatalysis - Photostability and Toxicity of Drugs and UV-Photoprotection - Solar Energy - Artificial Light Harvesting Systems - Photomedicine - Photo Nanosystems - Nano Tools for Solar Energy and Photochemistry - Solar Chemistry - Photochromism - Organic Light-Emitting Diodes - PV Systems - Nano Structured Solar Cells
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