Abstract
Exact models are a necessary prerequisite for optimal hardware configuration and the design of high-performance controllers. The photovoltaic system is considered a dynamic nonlinear multimodal system, where an optimization method must be used to resolve non-linearity and to identify the parameters describing the models of such systems. This has incited several researchers to work on and to develop several optimization methods. Recently, a number of methods have been proposed, including deterministic approaches, as well as probabilistic and stochastic numerical approaches, that aimed at obtaining a more accurate model for the PV cell and module array. This paper demonstrates the application of a performance optimization method based on discrete symbiotic organism search (DSOS), that mimics the behaviors of an organism in an ecosystem to survive. The high performance of such a method is attributable to the simplicity of the algorithm used; this algorithm is different from other heuristic algorithms, in that the GA needs two tuning parameters, i.e., the cross over and mutation rate, while the harmony search needs three rules to adjust and improvise new harmony, being memory consideration, pitch adjustment, and random choosing. Meanwhile, in the ABC algorithm, three phases are introduced to find the best food source, that is, the employed bee, the onlooker bee, and the scout bee phases, while the DSOS algorithm did not need any tuning parameters, wherein the proposed algorithm was used in both a single diode and double diode model across three test cases in the study. Compared to other previously published works, the level of performance of the algorithm is high in both implementation and accuracy; the DSOS algorithm is more capable of reaching the best set of solutions. The Mann-Whitney-Wilcoxon test to evaluate the discrete solutions of the algorithm for multiple runs with a 5% degree of confidence was evaluated and performed with a good level of accuracy.
Highlights
The continuous integration of renewable energy resources and the increased use of the photovoltaic system to generate green and efficient energy have given researchers more opportunities to study the generation of green power
This paper introduced a novel symbiosis organism search algorithm to solve the global optimization of nonlinear multimodal problems
The application of this algorithm was to estimate the electrical parameters of a solar cell and module array
Summary
The continuous integration of renewable energy resources and the increased use of the photovoltaic system to generate green and efficient energy have given researchers more opportunities to study the generation of green power. The goal has been to enhance the output from this energy source, as well as to enhance the efficiency of the panel. Over the last two decades, several countries have sought the benefits that these sustainable resources can supply. Photovoltaic energy is ubiquitous in rural and urban areas. Energies 2019, 12, 2246 topography, previously inaccessible villages have been electrified by photovoltaic systems.
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