Novel Runner-Root Algorithm based Maximum Power Point Tracking Approach for Permanent-Magnet Synchronous Generator Direct-Driven Wind Energy Conversion Systems

D. C. Huynh, Nam V. Pham, M. Dunnigan
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引用次数: 3

Abstract

This paper proposes a novel application of a runner-root (RR) algorithm for maximum power point tracking (MPPT) of a wind energy conversion system (WECS) direct-driven by a permanent magnet synchronous generator (PMSG). The WECS is required to operate at the MPP under varying wind conditions. The RR algorithm is the meta-heuristic algorithm, inspired by the function of runners and roots of some plants in nature. The plants are propagated through runners. They look for water resources and minerals by developing runners and roots. The RR algorithm is proposed to define maximum power points (MPP) corresponding to the optimal output voltage of the DC/DC boost converter of the PMSG-based WECS. The numerical results show that the RR algorithm based MPPT approach efficiently defines and tracks the MPPs of the PMSG-based WECS. A comparison with the hill-climb search (HCS) and particle swarm optimization (PSO) algorithms demonstrates the superiority of the RR algorithm and confirms its potential in the MPPT strategy of the PMSG-based WECS.
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基于Runner-Root算法的永磁同步发电机直接驱动风能转换系统最大功率点跟踪方法
提出了一种新的运行根(RR)算法在永磁同步发电机直接驱动的风能转换系统(WECS)最大功率点跟踪(MPPT)中的应用。wcs需要在不同的风况下在MPP运行。RR算法是一种元启发式算法,其灵感来自于自然界中一些植物的根和茎的功能。这些植物是通过植物体繁殖的。它们通过生长跑动体和根来寻找水资源和矿物质。提出了RR算法来定义基于pmsg的wcs的DC/DC升压变换器的最优输出电压对应的最大功率点(MPP)。数值结果表明,基于RR算法的MPPT方法能够有效地定义和跟踪基于pmsg的wcs的MPPT。通过与爬坡搜索(HCS)和粒子群优化(PSO)算法的比较,证明了RR算法的优越性,并证实了其在基于pmsg的wcs的最优定位策略中的潜力。
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