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光伏发电技术 MPPT ★ 5.0

增强太阳能无人机光伏系统能量供应的方法

Methods to Enhance the Energy Supply of Photovoltaic System for Solar-Powered Unmanned Aerial Vehicle

语言:

中文摘要

本文提出一种循环移位(CS)重构方案和两阶段最大功率点跟踪(TS-MPPT)方法,以提升太阳能无人机(SPUAV)光伏系统在部分遮阴条件下的能量供给能力。CS重构方案通过纵向移动光伏组件分散阴影,并推导最优移动距离,不仅提高了遮阴下的输出功率,还通过将全局最大功率点(GMPP)与右功率点(RPP)对齐简化了MPPT过程。TS-MPPT方法利用P-V曲线导数确定MPP位置,并通过求解线性方程交点实现快速跟踪,显著缩短响应时间并消除漂移现象。仿真与实验验证表明,相较于总交叉连接(TCT)结构,CS方案提升发电量25.65%;相比扰动观察法(P&O),TS-MPPT的启动时间和跟踪时间分别缩短60.6%和39.1%。

English Abstract

This article proposes a cyclic shift (CS) reconfiguration scheme and a two-stage maximum power point tracking (TS-MPPT) method to enhance the energy supply of solar-powered unmanned aerial vehicle (SPUAV) photovoltaic (PV) systems under partial shading conditions (PSCs). The proposed CS reconfiguration scheme disperses shadows by moving PV modules longitudinally and deduces the optimal movement distance. This scheme not only improves power delivery during PSCs but also simplifies the maximum power point tracking (MPPT) method by aligning the global maximum power point (GMPP) with the right power point (RPP). Furthermore, the proposed TS-MPPT method takes the derivative of the P–V curve to position the maximum power point (MPP) on the x-axis, and the MPP is tracked by solving the intersection points of the linear equation. The proposed method significantly reduces the tracking time and eliminates the drift phenomenon. The proposed reconfiguration scheme and the control method are simulated and experimentally verified under various PSCs. Results indicate that, compared to the total-cross-tied (TCT) scheme, the CS reconfiguration scheme enhances PV energy output by 25.65%. Compared to the perturb and observe (P&O) method, the TS-MPPT method reduced the start-up time and tracking time by 60.6% and 39.1%, respectively.
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SunView 深度解读

该文提出的TS-MPPT算法对阳光电源SG系列光伏逆变器具有重要应用价值。其基于P-V曲线导数判定MPP位置并通过线性方程交点快速跟踪的方法,可显著优化现有MPPT算法性能:启动时间缩短60.6%、跟踪时间减少39.1%,且消除漂移现象,这对提升逆变器在复杂遮阴场景下的发电效率至关重要。循环移位重构方案虽针对无人机应用,但其通过优化组件布局分散阴影、将GMPP与RPP对齐简化跟踪的思路,可启发阳光电源在分布式光伏系统设计中优化组串配置策略,并可集成到iSolarCloud智能诊断系统中,实现遮阴工况的预测性优化,提升1500V大型地面电站的整体发电量。