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An efficient tracking of MPP in PV systems using hybrid HCS-PS algorithm based ANFIS under partially shaded conditions

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Abstract

Rising electricity consumption and environmental pollution have encouraged electrical engineers to use photovoltaic (PV) systems at the power grid level. The use of PVs operating at their maximum power point can provide many benefits to power grids. This study proposes the maximum power point tracking control on the basis of the incremental conductance (INC) using the hybrid crow search and pattern search (HCS-PS) considering adaptive neuro-fuzzy inference system. The HCS-PS is employed to attain optimal voltages in various temperatures and irradiances circumstances. Then, the tracking cycle procedure is started using the INC method. Since the output power of PV systems is associated with uncertainties, the use of a storage system can be a great help in providing stable power in the network. The most benefits of the proposed approach include extraordinary efficiency, fast tracing, and stable performance. The usefulness of the recommended technique is confirmed using simulation results under various weather conditions.

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Funding

This study was not funded by any institution or organization.

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Authors and Affiliations

  1. School of Computer Sciences, Baoji University of Arts and Sciences, Baoji, 721007, China

    Xiaoe Wu & Hai Tao

  2. Solar Energy and Power Electronic Co., Ltd, Tokyo, Japan

    Noritoshi Furukawa & Hamid farajian

Authors
  1. Xiaoe Wu
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  2. Noritoshi Furukawa
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  3. Hai Tao
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  4. Hamid farajian
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Correspondence to Xiaoe Wu.

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Wu, X., Furukawa, N., Tao, H. et al. An efficient tracking of MPP in PV systems using hybrid HCS-PS algorithm based ANFIS under partially shaded conditions. Soft Comput 26, 5699–5717 (2022). https://doi.org/10.1007/s00500-022-06952-w

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  • DOI: https://doi.org/10.1007/s00500-022-06952-w

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