基于嵌入式学习算法的道路光伏最大功率点快速跟踪方法

Recent Developments in Photovoltaic Materials and Devices Pub Date : 2018-11-05 DOI:10.5772/INTECHOPEN.79711

K. Yamauchi

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引用次数: 1

摘要

本章提出了一种实现光伏路基最大功率点快速跟踪的新方法。用于道路光伏的pptdevice需要支持对移动物体引起的阴影闪烁的快速响应。我们提出的MPPT装置是一个连接到短PV串的微转换器。对于实际使用，连接到所提出的微转换器的几个pvstringset将并行连接。每个转换器都使用受昆虫大脑启发的嵌入式学习算法来学习ppsofasinglepvstring。因此，ppp设备通过摄动和观测方法在正常情况下跟踪smppp，学习机器学习获得的MPP与太阳辐照温度和强度之间的关系。因此，如果入射到pvpanel上的太阳光强度变化很快，学习机器就会产生预测的MPP来控制斩波电路。仿真结果表明，该方法可以实现快速的mppt。

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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A Quick Maximum Power Point Tracking Method Using an Embedded Learning Algorithm for Photovoltaics on Roads

This chapter presents a new approach to realize quick maximum power point tracking (MPPT)forphotovoltaics(PVs)beddedonroads.TheMPPTdevicefortheroadphotovoltaics needs to support quick response to the shadow flickers caused by moving objects. Our proposed MPPT device is a microconverter connected to a short PV string. For real-world usage,severalsetsofPVstringconnectedtotheproposedmicroconverterwillbeconnectedin parallel. Each converter uses an embedded learning algorithm inspired by the insect brain to learntheMPPsofasinglePVstring.Therefore,theMPPTdevicetracksMPPviatheperturba-tionandobservationmethodinnormalcircumstancesandthelearningmachinelearnsthe relationships between the acquired MPP and the temperature and magnitude of the Sun irradiation.Consequently,ifthemagnitudeoftheSunbeamincidentonthePVpanelchanges quickly, the learning machine yields the predicted MPP to control a chopper circuit. The simulationresults suggestedthat theproposed MPPTmethod canrealizequickMPPT.

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Recent Developments in Photovoltaic Materials and Devices

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