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Dual-Objective Optimization for Maximizing Photovoltaic Output Power in a Two-Stage Single-Phase Grid-Tied System

机译:在两级单相并网系统中实现光伏输出功率最大化的双目标优化

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摘要

The effective utilization of photovoltaic systems (PVS) is significantly affected by partial shading (PS). Although total cross-tied topology minimizes the power loss, the partial shading condition (PSC) decreases the output power generation and exhibits multiple power peaks in the Power Voltage characteristics. To address this issue, a dual-objective optimization technique based on reduced search space equilibrium optimization (RSS-EO) for a single-phase, two-stage gridconnected PVS, is presented. The proposed technique accomplishes two objectives 1) maximizing power generation by reconfiguring the PV modules using a switching matrix based on irradiance equalization and 2) extracting the global maximum power (GMP) with faster convergence, negligible steady-state oscillations, and reduced steady-state error. The simulation and experimental results validate the effectiveness of the proposed RSS-EO technique in efficiently distributing shade over the entire PV array and tracking GMP. The power enhancements achieved by RSS-EO, particle swarm optimization, and Munkres are 23.03, 20.02, and 19.01, respectively. Additionally, the proposed method exhibits an average mismatch power loss of 738 W, a fill factor of 58.1, and a percentage power loss of 26.83. Furthermore, the proposed algorithm is evaluated based on energy calculations and shows better performance by achieving the shortest payback period of 1.6 years.
机译:光伏系统(PVS)的有效利用受到部分遮阳(PS)的显著影响。尽管完全交叉拓扑将功率损耗降至最低,但部分阴影条件 (PSC) 会降低输出发电量,并在电源电压特性中表现出多个功率峰值。针对该问题,该文提出一种基于约化搜索空间均衡优化(RSS-EO)的单相双级并网PVS双目标优化技术。所提出的技术实现了两个目标:1)通过使用基于辐照度均衡的开关矩阵重新配置光伏组件,从而实现发电量的最大化;2)以更快的收敛速度、可忽略不计的稳态振荡和更小的稳态误差提取全局最大功率(GMP)。仿真和实验结果验证了所提RSS-EO技术在整个光伏阵列上有效分布阴影和跟踪GMP的有效性。RSS-EO、粒子群优化和Munkres实现的功率增强分别为23.03%、20.02%和19.01%。此外,所提方法的平均失配功率损耗为738 W,填充因子为58.1%,功率损耗百分比为26.83%。此外,所提出的算法基于能量计算进行评估,并通过实现1.6年的最短投资回收期显示出更好的性能。

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