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基于HAPSO算法的MPPT控制技术的研究
Research on MPPT Control Technology Based on HAPSO
投稿时间:2018-05-29  修订日期:2018-08-28
DOI:
中文关键词:  光伏系统  多峰PV曲线  最大功率点追踪(MPPT)  P&O算法  粒子群算法
英文关键词:Photovoltaic systems  Multi-peak PV curves  Maximum Power Point Tracking (MPPT)  P&O algorithm  PSO algorithm
基金项目:
作者单位E-mail
汪玉凤 辽宁工程技术大学电气与控制工程学院 252021919@qq.com 
王燚增 辽宁工程技术大学电气与控制工程学院 946118644@qq.com 
摘要点击次数: 113
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中文摘要:
      针对在光伏系统环境不断变化的时候,光伏的电压功率曲线(PV曲线)会出现多峰的现象,而传统的光伏最大功率追踪(MPPT)方法无法有效对其最大功率点进行追踪的问题。本文提出基于P&O以及经简化的加速粒子群算法的混合算法(HAPSO),这种方法不但能够有效的对光伏最大功率点进行追踪,而且通过对传统的粒子群算法进行简化以及加速,在确保高效率的前提下,简化控制系统的复杂度。并且通过半实物仿真实验系统验证了本文所提出算法的可行性,结果表明,本文所提出的HAPSO算法在确保高效率的同时,系统的整体设计复杂性与要求大大降低,除此之外,该方法的最大功率输出相对粒子群算法稳定,耐扰动能力也相对较强。
英文摘要:
      With the environment around photovoltaic system changing ,the PV curves will appear multi-peak phenomenon and in that case the traditional photovoltaic maximum power tracking(MPPT) methods can not track its maximum power point. For this problem ,this paper propose a hybrid method (HAPSO) which is based on the P&O algorithm and the simplified accelerated particle swarm optimization algorithm. With simplifying and accelerating the traditional particle swarm optimization algorithm, this method designed for photovoltaic maximum power point tracking can not only tracking the maximum photovoltaic power point effectively, but it can ensure that the algorithm can reduce the control system complexity with high efficiency. The feasibility of the proposed algorithm in tracking the maximum power point of the photovoltaic system is verified by a semi-physical simulation system. The results show that the proposed HAPSO algorithm ensures high efficiency while the overall design complexity and requirements of the system are greatly reduced. Additionally, the maximum power output with this method is relatively stable to the particle swarm algorithm, and its ability to withstand disturbances is quiet strong.
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