Modeling and Simulation of Photovoltaic Modules Using Bio-Inspired Algorithms

Abstract

This research aims to employ and qualify the bio-inspired algorithms: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution Algorithm (DE) in the extraction of the parameters of the circuit equivalent to a photovoltaic module in the models of a diode and five parameters (1D5P) and two diodes and seven parameters (2D7P) in order to simulate the I-V characteristics curves for any irradiation and temperature scenarios. The peculiarity of this study stands in the exclusive use of information present in the module’s datasheet to carry out the full extraction and simulation process without depending on external sources of data or experimental data. To validate the methods, a comparison was made between the data obtained by the simulations with data from the module manufacturer in different scenarios of irradiation and temperature. The algorithm bound to the model with the highest accuracy was DE 1D5P, with a maximum relative error of 0.4% in conditions close to the reference and 3.61% for scenarios far from the reference. On the other hand, the algorithm that obtained the worst result in extracting parameters was the GA in the 2D7P model, which presented a maximum relative error of 9.59% in conditions far from the reference.

Investigation of the Use of Evolutionary Algorithms for Modeling and Simulation of Bifacial Photovoltaic Modules

“…This phenomenon arises from the fact that the reference parameters are obtained from the technical sheet under STC conditions. The same characteristics can be observed in [15] where, according to the I-V curves were simulated in conditions far from the STC conditions, the accentuated error is visible by yourself. However, even choosing a more complex condition with G = 600 W/m 2 and Tc = 20 • C, the algorithms presented errors of less than 8%.…”

“…However, there are also models with greater complexity that are composed of a current source in parallel with two passive elements. These algorithms, despite being validated, tend to consume greater processing power and, in certain operating conditions, present greater errors [15]. Thus, the representation of energy generation from a photovoltaic module is carried out through simulations of photovoltaic electrical properties that are modeled by an electrical equivalence circuit [16].…”

Bio-Inspired Design of Future Solar Power Systems for Smart Grid Applications

“…Provensi et al, [27] address the challenge of evaluating photovoltaic module performance prior to deployment under different environmental conditions. The evaluation is done using photovoltaic modules provided in the manufacturer's data sheets.…”

“…The use of a bioinspired models from a geometrical viewpoint is yet to receive sufficient research consideration. In addition, the use of bio-inspired approaches is recognized to be useful in different aspects associated with solar cells, and solar panels as seen in [26][27][28][29]. Furthermore, the focus of the considered research is shown in Table 1.…”

A New MPPT-Based Extended Grey Wolf Optimizer for Stand-Alone PV System: A Performance Evaluation versus Four Smart MPPT Techniques in Diverse Scenarios

“…The diode current I d in a PV system can be calculated using the diode equation, which describes the current-voltage characteristic of a diode. The diode current can be expressed as follows [40]:…”