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Design of small photovoltaic power generation system based on maximum power point tracking

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<title>Design of small photovoltaic power generation system based on maximum power point tracking</title>
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<name type="personal" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20200023005">
<namePart>Cui, Yang </namePart>
<nameIdentifier>MAPA20200023005</nameIdentifier>
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<dateIssued encoding="marc">2020</dateIssued>
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<languageTerm type="code" authority="iso639-2b">eng</languageTerm>
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<abstract displayLabel="Summary">According to the nonlinear output characteristics of photovoltaic cells, combined with artificial intelligence algorithmthe the MPPTiMaximum Power Point Trackingjcontrol algorithm based on fuzzy variable step size is proposed, which enables the system to quickly track the maximum power point and improve the energy conversion efficiency of photovoltaic system.This paper designs a small-scale photovoltaic power generation system. The main circuit of the system consists of Perovskite Solar Panels, DC voltage regulator circuit, storage battery and one-way full bridge inverter circuit. The control circuit consists of sun-seeking, inverter and maximum power tracking on constant voltage. Proteus simulation software is used to simulate the sun-seeking part, the inverting part, the general control unit, the keys and the display interface. The results indicate that the functions of the small-scale photovoltaic power generation system can be achieved very well.</abstract>
<note type="statement of responsibility">Yang Cui...[Et al.]</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20110002916">
<topic>Energía fotovoltaica</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080553128">
<topic>Algoritmos</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080611200">
<topic>Inteligencia artificial</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20120007840">
<topic>Paneles solares</topic>
</subject>
<classification authority="">922.134</classification>
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<title>Revista Iberoamericana de Inteligencia Artificial</title>
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<publisher>IBERAMIA, Sociedad Iberoamericana de Inteligencia Artificial , 2018-</publisher>
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<identifier type="issn">1988-3064</identifier>
<identifier type="local">MAP20200034445</identifier>
<part>
<text>31/12/2020 Volumen 23 Número 66 - diciembre 2020 , p. 26-35</text>
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<recordCreationDate encoding="marc">201123</recordCreationDate>
<recordChangeDate encoding="iso8601">20220911190416.0</recordChangeDate>
<recordIdentifier source="MAP">MAP20200037255</recordIdentifier>
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