A New Three-point-based Approach for the Parameter Extraction of Photovoltaic Cells. (1st March 2019)

• Record Type: Journal Article
• Authors: Chin, Vun Jack; Salam, Zainal
• Is Part Of: Applied energy. Volume 237(2019)
• Page Start: 519
• Page End: 533
• Publication Date: 2019-03-01
• Subjects: Solar photovoltaic -- Parameter extraction -- Equivalent circuit model -- Pivot points -- Evolutionary algorithm; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.01.009
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A novel three-point-based parameter extraction method is introduced. The method is substantially more accurate compared to other relevant works. Moreover, it locates the optimal solution within very low number of iterations. The statistics over 35 runs indicate exceptionally consistent results. Abstract: This paper proposes a novel three-point based parameter extraction method for the single diode model. Unlike conventional curve-fitting procedures, the solution is simplistic yet exhibits outstanding ability to locate highly accurate solutions within very low number of iterations. The main idea is to establish three geometrically critical data points as the pivot points. By forcing the model to pass though these points exactly, the evolutionary algorithm (in this case differential evolution) is only utilized to fine-tune the remaining sections of the curve for best fit. As a result, the complexity of the algorithm is greatly reduced. A set of comparisons based on four case studies indicates that the proposed method substantially more accurate than other documented methods. Additionally, other tests with different types of photovoltaic modules (i.e. monocrystalline, polycrystalline, and thin film) at varying environmental conditions prove that the algorithm is reliable and practical for real-world applications. Besides, the scheme is highly efficient—it converges to the optimal solution in less than 50 iterations. Moreover, the solutions obtained are exceptionally consistent, i.e. the standard deviation of the root-mean-square error over 35 runs is at least 4 orders of magnitude less than those reported in other works. With these merits, the proposed method is envisaged to be valuable for both offline analysis and online monitoring applications where an accurate, fast and consistent parameter extraction tool is required.