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基于LS-SVM的光伏最大功率跟蹤控制方法
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國家自然科學(xué)基金資助項(xiàng)目(51077047),、江蘇省2010年研究生創(chuàng)新計(jì)劃資助項(xiàng)目(CX10B_267Z)和常州工學(xué)院校級(jí)科研基金資助項(xiàng)目(YN1302)


Research of MPPT Control Based on LS-SVM
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    摘要:

    為解決自然環(huán)境劇烈變化條件下,,傳統(tǒng)光伏最大功率跟蹤控制中存在的控制精度低和誤跟蹤現(xiàn)象,,建立了基于最小二乘支持向量機(jī)的最大工作點(diǎn)電壓預(yù)測模型,通過該模型預(yù)測光伏發(fā)電系統(tǒng)的最大工作點(diǎn)電壓,,并用預(yù)測電壓來修正恒電壓控制法的參考電壓,從而實(shí)現(xiàn)光伏發(fā)電系統(tǒng)的最大功率跟蹤控制,。仿真結(jié)果表明預(yù)測模型具有較高的精度,,相對(duì)誤差在0.04以內(nèi),控制方法能夠快速,、穩(wěn)定地實(shí)現(xiàn)光伏發(fā)電系統(tǒng)的最大功率跟蹤,,有效避免誤跟蹤現(xiàn)象。

    Abstract:

    In order to solve the low control accuracy and tracking error in the maximum power point tracing (MPPT) control in traditional photovoltaic, which was easily occurred under the natural dramatically changing environment, the paper presented a voltage predicting model based on least squares support vector machine (LS-SVM) for the prediction of the voltage of the maximum power output in the PV system, through which the maximum operating point voltage could be predicted, then the reference voltage of constant voltage control method could be modified and MPPT control of the PV system could be eventually realized. Simulation results showed that the model had higher accuracy in prediction, the relative error was less than 004, and the modified control method could guarantee maximum power tracking of the PV system quickly and stably, avoided the phenomenon of tracking error.

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蔡紀(jì)鶴,孫玉坤,李 蓓,徐 艷.基于LS-SVM的光伏最大功率跟蹤控制方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2014,45(S1):213-218. Cai Jihe, Sun Yukun, Li Bei, Xu Yan. Research of MPPT Control Based on LS-SVM[J]. Transactions of the Chinese Society for Agricultural Machinery,2014,45(S1):213-218.

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  • 收稿日期:2014-06-30
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  • 在線發(fā)布日期: 2014-11-15
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