ADALINE Based Maximum Power Point Tracking Methods for Stand-Alone PV Systems Control

被引：4
|
作者：
Triki, Yacine [1 ,2 ]
Bechouche, Ali [1 ]
Seddiki, Hamid [1 ]
Abdeslam, Djaffar Ould [2 ]
Wira, Patrice [2 ]
机构：
[1] Mouloud Mammeri Univ Tizi Ouzou, L2CSP Lab, BP 17 RP, Tizi Ouzou 15000, Algeria
[2] Haute Alsace Univ, MIPS Lab, 61 Rue Albert Camus, F-68093 Mulhouse, France
来源：
2018 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY (ICIT) | 2018年
关键词：
Adaptive linear neuron; boost converter; maximum power point tracking; perturbe & observe algorithm; photovoltaic;
D O I：
10.1109/ICIT.2018.8352294
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
This paper presents two novel methods for maximum power point (MPP) tracking of a stand-alone PV system. The proposed techniques are based on adaptive linear neuron strategy. Their performances are evaluated through simulation tests, considering different irradiance profiles according to the Standard EN 50530 Test recommendations. The system, including boost converter, is capable to tracking MPPs accurately and quickly without power loss. Proposed methods are compared with the conventional P&O algorithm under different operation conditions. Obtained results proven that the proposed methods are better than the P&O algorithm which fails under rapid irradiance change.
引用
收藏
页码：880 / 885
页数：6
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