An improved PSO algorithm for high accurate parameter identification of PV model

Lili Gong, W. Cao, Jianfeng Zhao
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引用次数: 12

Abstract

Accurate and practical photovoltaic (PV) models are very important for simulation of PV power systems. However, it is complicated to extract all PV model parameters due to limited information. With the aim of improving accuracy and reducing complexity, this paper proposes a novel method based on particle swarm optimization (PSO) algorithm to determine the unknown PV model parameters. To obtain the output characteristics of PV under different conditions, the I-V equation for PV model with only one unknown parameter is introduced. The PSO technology is applied for parameter identification, which adopts some improvements in the iterative process to ensure the effective convergence. The improved PSO-based method is verified with PV modules of different technologies.
一种改进的粒子群算法用于PV模型的高精度参数辨识
准确实用的光伏模型对光伏发电系统的仿真非常重要。然而,由于信息有限,提取所有PV模型参数比较复杂。为了提高精度和降低复杂度,本文提出了一种基于粒子群优化(PSO)算法的未知PV模型参数确定方法。为了得到PV在不同条件下的输出特性,引入了只有一个未知参数的PV模型的I-V方程。采用粒子群技术进行参数辨识,在迭代过程中进行了改进,保证了算法的有效收敛。用不同工艺的光伏组件对改进后的pso方法进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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