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A proposed adaptive step size perturbation and observation maximum power point tracking algorithm based on photovoltaic system modeling.

机译:提出了一种基于光伏系统建模的自适应步长摄动和观测最大功率点跟踪算法。

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摘要

Solar energy becomes one of the major alternative renewable energy options for its huge abundance and accessibility. Due to the intermittent nature, the high demand of Maximum Power Point Tracking (MPPT) techniques exists when a Photovoltaic (PV) system is used to extract energy from the sunlight. This thesis proposed an advanced Perturbation and Observation (P&O) algorithm aiming for relatively practical circumstances. Firstly, a practical PV system model is studied with determining the series and shunt resistances which are neglected in some research. Moreover, in this proposed algorithm, the duty ratio of a boost DC-DC converter is the object of the perturbation deploying input impedance conversion to achieve working voltage adjustment. Based on the control strategy, the adaptive duty ratio step size P&O algorithm is proposed with major modifications made for sharp insolation change as well as low insolation scenarios. Matlab/Simulink simulation for PV model, boost converter control strategy and various MPPT process is conducted step by step. The proposed adaptive P&O algorithm is validated by the simulation results and detail analysis of sharp insolation changes, low insolation condition and continuous insolation variation.
机译:太阳能以其丰富的资源和可及性而成为主要的可替代可再生能源选择之一。由于间歇性,当使用光伏(PV)系统从阳光中提取能量时,对最大功率点跟踪(MPPT)技术存在很高的要求。针对相对实际的情况,本文提出了一种先进的摄动和观测(P&O)算法。首先,通过确定一些研究中忽略的串联电阻和分流电阻来研究实用的光伏系统模型。此外,在该算法中,升压DC-DC转换器的占空比是微扰的目的,其采用输入阻抗转换来实现工作电压调整。在控制策略的基础上,提出了自适应占空比步长P&O算法,并针对日照急剧变化以及日照不足的情况进行了重大修改。逐步进行光伏模型的Matlab / Simulink仿真,升压转换器控制策略和各种MPPT过程。仿真结果和日照变化剧烈,日照条件低,日照变化连续的详细分析结果验证了所提出的自适应P&O算法的有效性。

著录项

  • 作者

    Huang, Yu.;

  • 作者单位

    State University of New York at Buffalo.;

  • 授予单位 State University of New York at Buffalo.;
  • 学科 Engineering Electronics and Electrical.;Energy.
  • 学位 M.S.
  • 年度 2014
  • 页码 66 p.
  • 总页数 66
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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