article · Applied Sciences
This research proposes a novel model, the modified three-diode model (MTDM), for multi-crystalline silicon solar cells (MCSSCs) to more accurately represent their electrical behaviour. This model extends a previously modified double-diode model by incorporating an additional diode to account for defect regions within the solar cell. To estimate the parameters of this new MTDM, two metaheuristic algorithms, Closed-Loop Particle Swarm Optimisation (CLPSO) and Elephant Herd Optimisation (EHO), were developed for their superior convergence rates. The models were tested using experimental data from MCSSCs under varying irradiance and temperature conditions. Simulation results indicate that the MTDM provides more accurate solutions for MCSSCs compared to existing models, with EHO outperforming CLPSO in terms of solution quality and convergence.
Accurate modelling of solar cells is crucial for optimising their performance and efficiency. This research offers a more precise way to understand and predict how multi-crystalline silicon solar cells behave, which can lead to better design and operation of solar energy systems.
This research provides an improved modelling tool for multi-crystalline silicon solar cells. It could enable solar cell manufacturers and researchers to design more efficient and reliable solar panels by offering a more accurate simulation of cell behaviour. This appears to be early-stage research focused on model development and validation, rather than a near-market product.
AI-generated from the published abstract. Always read the original work before citing.
Recently, the use of multi-crystalline silicon solar cells (MCSSCs) has been increasing worldwide. This work proposes a novel MCSSC pattern for achieving a more accurate emulation of the electrical behavior of solar cells. Specifically, this pattern is dependent on the modification of the double diode model of MCSSCs. Importantly, the proposed pattern has an extra diode compared to the previously modified double-diode model (MDDM) described in the literature for considering the defect region of MCSSC to form a modified three diode model (MTDM). For estimating the parameters of the proposed MTDM, two metaheuristic algorithms called closed-loop particle swarm optimization (CLPSO) and elephant herd optimization (EHO) are developed, which have superior convergence rates. The competitive algorithms are executed on experimental data based on a MCSSC of area 7.7 cm2 from Q6-1380 and CS6P-240P solar modules under different irradiance and temperature levels for both MDDM and MTDM. Also, the proposed elephant herd optimization soft paradigm is extended for a high irradiance level at 1000 W/m2 on an R.T.C. France Solar cell. The proposed new optimization models are more efficient in dealing with the natural characteristics of the MCSSC. The simulation results show that the MTDM gives more accurate solutions as a model to the MCSSC compared with the results reported in the literature. From the viewpoint of soft computing paradigms, the EHO outperforms CLPSO in terms of the solution quality and convergence rates.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.3390/app11031055
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
