文章基本信息

标题：Parametric estimation in photovoltaic modules using the crow search algorithm
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作者：Oscar Danilo Montoya ; Carlos Alberto Ramírez-Vanegas ; Luis Fernando Grisales-Noreña 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2022
卷号：12
期号：1
页码：82-91
DOI：10.11591/ijece.v12i1.pp82-91
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：The problem of parametric estimation in photovoltaic (PV) modules considering manufacturer information is addressed in this research from the perspective of combinatorial optimization. With the data sheet provided by the PV manufacturer, a non-linear non-convex optimization problem is formulated that contains information regarding maximum power, open-circuit, and short-circuit points. To estimate the three parameters of the PV model (i.e., the ideality diode factor (a) and the parallel and series resistances (Rp and Rs)), the crow search algorithm (CSA) is employed, which is a metaheuristic optimization technique inspired by the behavior of the crows searching food deposits. The CSA allows the exploration and exploitation of the solution space through a simple evolution rule derived from the classical PSO method. Numerical simulations reveal the effectiveness and robustness of the CSA to estimate these parameters with objective function values lower than 1 × 10−28 and processing times less than 2 s. All the numerical simulations were developed in MATLAB 2020a and compared with the sine-cosine and vortex search algorithms recently reported in the literature.
关键词：Crow search algorithm;Manufacturer information;Metaheuristic optimization;Parametric estimation;Photovoltaic modules;Single-diode model