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  • 學位論文

基於仿生物群追蹤演算法之太陽能最大功率追蹤器的研製

Design and Implementation of Maximum Power Point Tracker for PV System Based upon Biological Swarm Chasing Algorithm

指導教授 : 賴炎生 陳良瑞
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摘要


本論文乃針對整合模組化的太陽能供電系統,提出一個基於仿生物群追蹤行為的太陽能最大功率點追蹤方式,用以增進最大功率點追蹤之性能。每一個太陽能模組均視為一個粒子,而最大功率點為移動的目標且被視為群體的最佳解。因此,每一個太陽能模組均能自動地追蹤最大功率點。最後,本論文使用三塊175W 的太陽能模組並接成的525W 原型機,用來評估其最大功率點追蹤之性能。與典型的擾動觀察最大功率追蹤法相比較,如本論文所提出的仿生物群最大功率點追蹤理論之預測,在暫態時,最大功率點追蹤的效率改善了12.19%。

並列摘要


In this thesis, a novel photovoltaic (PV) maximum power point tracking (MPPT) based on biological swarm chasing behavior is proposed to increase the MPPT performance for a module-integrated PV power system. Each PV module is viewed as a particle, and as a result, the maximum power point is viewed as the moving target. Thus, every PV module can chase the maximum power point (MPP) automatically. A 525W prototype constructed by three paralled-connected 175W PV modules is implemented to assess the MPPT performance. Comparing with a typical perturb and observe (P&O) MPPT method, the MPPT efficiency is improved about 12.19% in transient state by the proposed MPPT as theoretical prediction.

參考文獻


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