The existing research on estimating solar cell parameters mainly focuses on minimizing the Root-Mean-Square Error () between the estimated and measured current values of solar cells (referred to as the ). This involves using an analytical expression for current - as a function of voltage - ( = ()) expressed through the Lambert function. This paper introduces a new analytical solution for calculating the between measured and estimated solar cell voltages (referred to as the ). The formula is derived using the -function or LogWright function, which provides a numerically applicable method for representing the analytical relation between solar cell voltage and current ( = ()). Moreover, the paper presents the original formulas for calculating Mean Absolute Error () and Mean Absolute Percentage Error () for solar cell voltages expressed through the -function. The paper also compares various published approaches and examines two well-known solar cells/modules, namely the RTC France solar cell and the SOLAREX MSX-60 PV solar module, in terms of the and single-diode solar cell models. Additionally, a novel metaheuristic algorithm, known as the Chaotic Walrus Optimization Algorithm (Chaotic-WaOA), is proposed for solar cell parameter estimation. This algorithm is applied to both mentioned solar cells to determine their parameters in terms of minimal . In order to verify the proposed research, experimental observations were conducted on a 60Wp monocrystalline solar module installed at the Faculty of Sciences and Mathematics in Niš, Serbia. This was done using a specialized PV-KLA apparatus under different outdoor conditions. The research was also verified with a Cadmium telluride solar module (CdTe75638) and a multi-crystalline silicon solar module (mSi0188). The investigation results demonstrate the accuracy, applicability, and numerical feasibility of the proposed expression and algorithm. Additionally, the study confirms the applicability of the g-function in invertible solar cell modeling.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11422038 | PMC |
http://dx.doi.org/10.1016/j.heliyon.2024.e37887 | DOI Listing |
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