Parametric estimation in photovoltaic modules using the crow search algorithm
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Date
2021-06-16
Authors
Montoya, Oscar Danilo
Ramírez-Vanegas, Carlos Alberto
Grisales-Noreña, Luis Fernando
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Abstract
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.
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Citation
Montoya Giraldo, Oscar & Ramírez-Vanegas, Carlos & Grisales-Noreña, Luis. (2022). Parametric estimation in photovoltaic modules using the crow search algorithm. International Journal of Electrical and Computer Engineering. 12. 82-91. 10.11591/ijece.v12i1.pp82-91.