基于元启发式优化方法的光伏组件参数估计

Danilo de Oliveira Pimentel, Marcelo Cabral Cavalcanti, F. Bradaschia, Eduardo José Barbosa, Leonardo Rodrigues Limongi
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引用次数: 1

摘要

本文对光伏组件的全局非线性模型进行了评价。本文以光伏组件单二极管电路为研究对象,通过对模式搜索(PS)、粒子群优化(PSO)和进化粒子群优化(EPSO)算法在光伏组件模型参数估计过程中的精度进行比较研究。首先提出了全局非线性模型,并使用PS优化方法对其参数进行估计,因此有必要在模型参数估计过程中评估新的优化方法。因此,以功率平均绝对误差(MAEP)作为单晶硅、多晶硅、非晶硅、碲化镉光伏组件技术的比较指标,对全局非线性模型和优化方法的精度进行了评价,即通过与实验曲线的比较,预测I- V和P- V曲线行为的能力。结果表明,随机元启发式优化方法能较好地估计评估后的光伏组件模型的参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Parameters Estimation of Photovoltaic Modules Using Optimization Methods Based on Metaheuristics
This paper deals to evaluate a model already developed for photovoltaic (PV) modules, called global nonlinear model. Based in electrical circuit of a single-diode for PV modules' the main goal is to perform through a comparative study of precision with applying the optimization methods Pattern Search (PS), Particle Swarm Optimization (PSO) and Evolutionary Particle Swarm Optimization (EPSO) in the process of parameters estimating in the PV module model. The global nonlinear model was initially proposed with a process for estimating its parameters using the PS optimization method, therefore, it is necessary to evaluate new optimization methods in the parameter estimation process of this model. Therefore, the precision of the global nonlinear model and optimization methods were evaluated, that is, its ability to predict the behavior of I- V and P- V curves based on comparison with experimental curves, using the Mean Absolute Error in Power (MAEP) as a comparative indicator for the PV module technologies of mono crystalline silicon, polycrys-talline silicon, amorphous silicon, cadmium telluride. The results showed that stochastic metaheuristic optimization methods can lead to good results in estimating the parameters of the evaluated PV modules model.
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