基于功率点跟踪的变速微水力发电最大化

M. K. Tan, Norafe Maximo Javinez, Kit Guan Lim, A. Haron, Pungut Ibrahim, K. Teo
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引用次数: 0

摘要

传统的变速微水力控制系统存在非最优输入控制的问题。控制器在不预测全局最大功率曲线的情况下估计流量的变化。因此,本文旨在探索和开发一种可行的具有摄动与观测(P&O)和遗传算法(GA)的最大功率点跟踪器(MPPT),为变速微水电系统提供最优发电。本文首先介绍了实验用变速微水力平台的数学模型,然后在MATLAB中对微水力平台进行了仿真。传统的P&O MPPT算法采用固定的扰动大小,当扰动大小较小时计算时间较大,当扰动大小较大时存在功率波动问题。为此,提出了一种基于遗传算法的扰动大小自适应的P&O MPPT算法,在瞬态响应时提供大的扰动大小,在稳态时提供小的扰动大小。仿真结果表明,基于遗传算法的P&O最大功率跟踪算法能够跟踪全局最大功率点(MPP)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Maximizing Power Generation in Variable Speed Micro-Hydro with Power Point Tracking
Conventional variable speed micro-hydro control systems suffer from non-optimal input control. The controllers estimate the changes in flow rate without anticipating the global maximum power curve. As such, this paper aims to explore and develop a feasible maximum power point tracker (MPPT) with perturb and observe (P&O) and genetic algorithm (GA) in providing optimal power generation for variable speed micro-hydro system. This research first introduces a mathematical model for an experimental variable speed micro-hydro platform and then simulates the micro-hydro in MATLAB. Conventional P&O MPPT algorithm used fixed perturbation size which requires large computation time when the perturbation size is small and suffers from power fluctuation issues when the perturbation size is large. Thus, a GA-based P&O MPPT algorithm with adaptive perturbation size is proposed to provide a large perturbation size during transient response and a small perturbation size at a steady state. The simulation results showed that the proposed GA-based P&O MPPT algorithm was able to track the global maximum power point (MPP).
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