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A new MPPT design using PV-BES system using modified sparrow search algorithm based ANFIS under partially shaded conditions

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Abstract

Nowadays, due to the increasing interest in renewable energy, modeling and practical research on Photovoltaic (PV) have been given much attention. Currently, the challenge of using PV systems is to reach the maximum power point (MPP) in order to increase their efficiency. Hence, extensive research has been done all over the world to develop the productivity of the PV system by properly tracking the MPP. In this regard, in this article, a new maximum power point tracking (MPPT) technique based on Modified Sparrow Search Algorithm and adaptive neuro-fuzzy inference system (ANFIS) is suggested. To implement the suggested MPPT method, two important steps must be taken into account. Firstly, in different conditions of radiation and temperature, the optimal voltage is obtained by mSSA algorithm. Then, the optimal voltage is achieved by the proposed ANFIS method based on different radiation conditions to find the MPP. In order to evaluate the proposed MPPT technique, simulations are done in MATLAB in different weather conditions and scenarios. The results indicate the suitable performance of the recommended mSSA-ANFIS-based MPPT controller in tracking the MPP and achieving the global optimum in different weather conditions by attaining 99.3% efficiency.

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Correspondence to Mohsen Latifi.

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Appendix A

Appendix A

See Table 2

Table 2 Detailed model

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Alaas, Z., Eltayeb, G.e.A., Al-Dhaifallah, M. et al. A new MPPT design using PV-BES system using modified sparrow search algorithm based ANFIS under partially shaded conditions. Neural Comput & Applic 35, 14109–14128 (2023). https://doi.org/10.1007/s00521-023-08453-9

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