Mohammad Faridun Naim Tajuddin
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Preferred name
Mohammad Faridun Naim Tajuddin
Official Name
Mohammad Faridun Naim , Tajuddin
Alternative Name
Tajuddin, Mohd Faridun Naim
Tajuddin, Mohd
Tajuddin, Mohammad Faridun Naim
Tajuddin, M. F.N.
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Scopus Author ID
35590716200
Researcher ID
GSD-2139-2022

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  • Publication
    Optimal extraction of photovoltaic energy using fuzzy logic control for maximum power point tracking technique
    (Institute of Advanced Engineering and Science (IAES), 2020-07)
    Kadhim Hamzah Chalok
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Thanikanti Sudhakar Babu
    ;
    Shahrin Md Ayob
    ;
    Tole Sutikno
    In photovoltaic (PV) systems, maximum power point tracking (MPPT) techniques are used to track the maximum power from the PV array under the change in irradiance and temperature conditions. The perturb and observe (P&O) is one of the most widely used MPPT techniques in recent times due to its simple implementation and improved performance. However, the P&O has limitations such as oscillation around the MPP during which time the P&O algorithm will become confused due to rapidly changing atmospheric conditions. To overcome the above limitation, this paper uses the fuzzy logic controller (FLC) to track the maximum power from the PV system under different irradiance, integrates it with a DC-DC boost converter as a tracker. The result of the FLC performance is compared with the traditional P&O method and shows the MPPT algorithm based on FLC ensures continuous tracking of the maximum power within a short period compared with the traditional P&O method. Besides that, the proposed method (FLC) has a faster dynamic response and low oscillations at the operating point around the MPP under steady-state conditions and dynamic change in irradiance.
  • Publication
    Hybrid salp swarm maximum power point tracking algorithm for photovoltaic systems in highly fluctuating environmental conditions
    (Nature Research, 2025-03)
    Mohd Nasrul Izzani Jamaludin
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Tarek Younis
    ;
    Sudhakar Babu Thanikanti
    ;
    Mohammad Khishe
    The maximum power delivered by a photovoltaic system is greatly influenced by atmospheric conditions such as irradiation and temperature and by surrounding objects like trees, raindrops, tall buildings, animal droppings, and clouds. The partial shading caused by these surrounding objects and the rapidly changing atmospheric parameters make maximum power point tracking (MPPT) challenging. This paper proposes a hybrid MPPT algorithm that combines the benefits of the salp swarm algorithm (SSA) and hill climbing (HC) techniques. As long as the rate of change of irradiance does not exceed a specific limit, the HC mode is applied to track the global maximum power point (GMPP). Once a high rate of change in irradiation is detected, the SSA mode is activated. Moreover, the proposed algorithm employs the concept of boundary conditions to handle fast and slow fluctuating irradiance patterns. A comprehensive comparative evaluation of the proposed hybrid SSA-HC with state-of-the-art MPPT algorithms has been undertaken. Four distinct cases have been examined, including irradiance conditions with varying rates of change and partial shading conditions. The proposed hybrid SSA-HC algorithm has been validated and tested using a developed hardware setup, simulated in MATLAB for solar photovoltaic (PV) systems, and compared with standard SSA and HC. The performance of the tracking capability of this proposed hybrid technique at both steady-state and dynamic conditions under rapid and gradual irradiance changes demonstrates its superiority over recent state-of-the-art algorithms.