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Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering

Annals of Computer Science and Information Systems, Volume 33

A hybrid method based MPP tracking strategy for solar power systems

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DOI: http://dx.doi.org/10.15439/2022R29

Citation: Proceedings of the 2022 Seventh International Conference on Research in Intelligent and Computing in Engineering, Vu Dinh Khoa, Shivani Agarwal, Gloria Jeanette Rincon Aponte, Nguyen Thi Hong Nga, Vijender Kumar Solanki, Ewa Ziemba (eds). ACSIS, Vol. 33, pages 171–176 ()

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Abstract. One of the key factors used to measure the efficiency of a solar power system is the convergence time during the MPP tracking. In other words, the number of duty ratio samples should be as low as possible. In particular, the MPP tracking takes a long time and easily falls into the local MPP when the PV system is partially shaded, which reduces the operational efficiency of the PV system. The incremental conductance (In-Cond) algorithm and the improved grey wolf optimization (GWO) method have been combined to provide a novel approach for a standalone PV power system to overcome this drawback. In the proposed methodology, the global MPP is searched using the hybrid method, which is integrated the improved GWO with the In-Cond algorithm. To demonstrate the feasibility of the proposed method, MATLAB simulations the PV system are provided. The global MPP is not only obtained under uniform irradiance, but also under partial shading influences.

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