Mohammad Faridun Naim Tajuddin
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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
    Power Generation Improvement using Active Water Cooling for Photovoltaic (PV) Panel
    ( 2021-01-01)
    Mohamad Shukor Abdul Rahim
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Mohd Sazli Saad
    ;
    Nalini C.
    ;
    Edaris Z.L.B.
    ;
    Hasanuzzaman M.
    Photovoltaic (PV) cooling systems are commonly used to improve photovoltaic panels power generation and efficiency. Photovoltaic (PV) panels require irradiance to generate power, although increasing irradiance is often correlated with increasing temperature. These rapid increases of temperature in photovoltaic (PV) panels severely affect the power conversion operation. With a proper cooling process on its surface, a solar photovoltaic (PV) system can operate at a higher efficiency. This research aims to study the power improvement of active water-cooling on photovoltaic (PV) panels. A fixed minimum water flow of 5.80 l/min is sprayed onto the panel's front surface to reduce the temperature. The sprayed water created a thin water film and managed to reduce the temperature. Other than that, there is also reference photovoltaic (PV) panel, which is a panel without any cooling system. The outputs compared are the module temperature, maximum output power, open circuit voltage, and short circuit current. As the irradiance starts increasing, the panel temperature also begins to spike. However, with active water cooling, the temperature was able to be reduced by 37.67% during the day's hottest temperature. This reduction of temperature creates power improvement to the cooled panel up to 253W, compared to the reference panel output of only 223W. During the overheating of a photovoltaic (PV) panel, the open circuit voltage was found to be the most affected. This increase in power with active water cooling can potentially have a massive impact on large-scale photovoltaic (PV) panel installations.
  • Publication
    Fundamental study on the impacts of water-cooling and accumulated dust on photovoltaic module performance
    ( 2022-12-01)
    Alwesabi F.A.A.
    ;
    Aziz A.S.
    ;
    Mohamad Shukor Abdul Rahim
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Mohd Fayzul Mohammed
    ;
    Azralmukmin Azmi
    ;
    Satterlee C.
    ;
    Ayob S.M.
    ;
    Sutikno T.
    Photovoltaic (PV) modules have been becoming well-spread recently as alternative clean energy sources to traditional energy sources due to their efficiency and sustainability benefits. This paper applied various water temperatures and artificial dust levels to a couple of monocrystalline PV modules under outdoor conditions to observe their performance. Two different IV tracers were connected separately to each module for comparison purposes. Two temperature sensors were installed at the back of the panels to observe the cell temperatures. Besides, a temperature sensor was specified for ambient readings. Water flowed through an adjustable water-flow sensor to cool the overheated PV module using specific mass flow rates. The results indicate that the efficiency of the PV module starts to reduce when the panel temperature begins to surpass 49.1°C. It was discovered that cooling the PV module increases its efficiency from 0.97 percent at the lowest rate to 4.70 percent at the highest rate. Furthermore, accumulated dust on the PV module top surface can be reduced up to 3-fold under 110 g/m2 of dust, and up to 29.30% under 10 g/m2 of 100% of its generated energy. Improvement techniques and future work on PV module performance are also discussed.
  • Publication
    MPP Tracking with a Modified Duty Cycle Sweeping (MDCS) Algorithm for Various Environmental Irradiance Conditions
    ( 2023-01-01)
    Mohd Asri Jusoh
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Roslan M.A.
    In this paper, a photovoltaic (PV) system based on modified duty cycle sweeping (MDCS) has been proposed to achieve the maximum power point tracking (MPPT). The disadvantages of perturb and observe (P&O), such as diverging tracking directions and the inability to detect the global peak during partial shading (PS), are intended to be overcome by this method (PS). An intelligent double identification and tracking method consistently tracks the global peak under partial shading and the MPP under rapid irradiance fluctuations. Strict dynamic irradiance and partial shading tests are imposed in MATLAB/Simulink@ and simulated to validate the suggested concept. Additionally, a laboratory prototype MPPT standalone PV system supported by Texas Instruments' Code Composer Studio is operated by a SEPIC converter in conjunction with the C2000 real-time microcontroller in order to conduct an experimental validation study. The effectiveness of the method is compared with the other well-known MPPT techniques, conventional P&O. The suggested method successfully follows the global peak under various patterns of partial shading as compared to the conventional algorithms. The algorithm's efficiency has been preserved at around 95-100%.
  • Publication
    Control strategies of power electronic converter for grid-tied variable low-speed wind turbine
    (AIP Publishing Ltd., 2023)
    Hussein Shutari
    ;
    Nordin Saad
    ;
    Nursyarizal Bin Mohd Nor
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Muawai Magzoub
    With the increased penetration of wind energy on modern power systems, Wind Energy Conversion Systems (WECS) are required to participate actively in capturing the maximum wind energy and operating electric networks through a suitable control strategy. This paper provides the design and implementation of control strategies for Fully Controlled Power Electronic Converter (FCPEC) associated with a Variable Low-speed Wind Turbine (VLSWT) system. The considered system consists of a Wind Turbine (WT) and Permanent Magnet Synchronous Generator (PMSG) that are linked to the grid via an FCPEC. The control schemes of the FCPEC include a Maximum Power Point Tracking (MPPT) algorithm, a Machine Side Converter (MSC) control, and a Grid Side Inverter (GSI) control. To validate the effectiveness of the implemented control strategies, the considered system was modelled and simulated using MATLAB/Simulink under Malaysia wind speed profiles (2 m/s - 6 m/s). The simulation results proved that the MPPT algorithm and MSC control have successfully forced WT to operate at the optimal power coefficient of 0.44 further improved the maximum power available from the wind system that can be obtained. Besides, the results showed the capability of the GSI controller in improving the system performance in both steady-state and disturbance operating conditions. The dc-link voltage regulation and power integration to grid, with a unity power factor regardless of wind speed variation, were successfully accomplished.
  • Publication
    Improved hill climbing algorithm with fast scanning technique under dynamic irradiance conditions in photovoltaic system
    (IOP Publishing, 2020)
    Ali Jawad Khadhim Alrubaie
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Tekai Eddine Khalil Zidane
    ;
    Azralmukmin Azmi
    The perturb and observe (P&O) algorithm is an easy and effective method used for tracking maximum power point. However, this technique suffers from deviation when irradiation changes suddenly. Moreover, the impact of this deviation is high when the insolation variation is rapid. This error is due to the incorrect decision taken by the conventional P&O method throughout the first step-change in the duty cycle during the increase in irradiation. The proposed P&O is a modified conventional P&O that focuses on using additional dI parameter with variable step size ΔDn. In this manner, the conventional P&O algorithm is allowed to identify the source of deviation caused by rapid irradiance changes. The efficiency of the proposed P&O is assessed using simulation in MATLAB/Simulink. Results show that the proposed P&O effectively tracks maximum power and prevents deviations in rapidly changing climate conditions within a short time, which is lesser than the conventional P&O method. In addition, the proposed P&O has a rapid dynamic response. A DC–DC boost converter is utilized in this work to validate the proposed P&O algorithm.
  • 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.
  • Publication
    Integrating deep transfer learning and image enhancement for enhancing defective photovoltaic cells classification in electroluminescence images
    (Iran University of Science and Technology, 2025-06)
    Aimi Salihah Abdul Nasir
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Kumuthawathe Ananda-Rao
    ;
    Hanim Suraya Mohd Mokhtar
    ;
    Muhammad Hafeez Abdul Nasir
    The rapid growth of photovoltaic (PV) systems has highlighted the need for efficient and reliable defect detection to maintain system performance. Electroluminescence (EL) imaging has emerged as a promising technique for identifying defects in PV cells; however, challenges remain in accurately classifying defects due to the variability in image quality and the complex nature of the defects. Existing studies often focus on single image enhancement techniques or fail to comprehensively compare the performance of various image enhancement methods across different deep learning (DL) models. This research addresses these gaps by proposing an in-depth analysis of the impact of multiple image enhancement techniques on defect detection performance, using various deep learning models of low, medium, and high complexity. The results demonstrate that mid-complexity models, especially DarkNet-53, achieve the highest performance with an accuracy of 94.55% after MSR2 enhancement. DarkNet-53 consistently outperformed both lower-complexity models and higher-complexity models in terms of accuracy, precision, and F1-score. The findings highlight that medium-depth models, enhanced with MSR2, offer the most reliable results for photovoltaic defect detection, demonstrating a significant improvement over other models in terms of accuracy and efficiency. This research provides valuable insights for optimizing defect detection systems in photovoltaic applications, emphasizing the importance of both model complexity and image enhancement techniques for robust performance.
  • Publication
    Two-terminal fault detection and location for hybrid transmission circuit
    ( 2021-08-01)
    Muhd Hafizi Idris
    ;
    Mohd Rafi Adzman
    ;
    Mokhlis H.
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Haziah Abdul Hamid
    ;
    Melaty Amirruddin
    This paper presents the algorithms developed to detect and locate the faults at a hybrid circuit. First, the fault detection algorithm was developed using the comparison of total positive-sequence fault current between pre-fault and fault times to detect the occurrence of a fault. Then, the voltage check method was used to decide whether the fault occurred at overhead line (OHL) or cable section. Finally, the fault location algorithm using the impedance-based method and negative-sequence measurements from both terminals of the circuit were used to estimate the fault point from local terminal. From the tests of various fault conditions including different fault types, fault resistance and fault locations, the proposed method successfully detected all fault cases at around 1 cycle from fault initiation and with correct faulted section identification. Besides that, the fault location algorithm also has very accurate results of fault estimation with average error less than 1 km and 1%.
      11  33
  • Publication
    Experimental study on modified GOA-MPPT for PV system under mismatch conditions
    ( 2024)
    Nur Afida Muhammad
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Azralmukmin Azmi
    ;
    Mohd Nasrul Izzani Jamaludin
    ;
    Shahrin Md Ayob
    ;
    Tole Sutikno
    This paper presents a modified grasshopper optimization algorithm (GOA) tailored for optimizing the power extraction capability of a solar photovoltaic (PV) system. The algorithm`s focus is on addressing one of the issues associated with mismatch loss (MML), particularly the mismatch (MM) in solar irradiance conditions, to attain maximum output power. The core strategy of the GOA involves optimizing the duty cycles of the converter to achieve the maximum power point (MPP) for the PV system. The PV system configuration comprises three PV modules connected in series and a SEPIC converter. To facilitate efficient maximum power point tracking (MPPT), the paper proposes using the GOA as a controlling mechanism. The study employs a comparative approach, contrasting the performance of the proposed system against established algorithms, such as PSO and GWO. The results of these evaluations exhibit the superior performance of the proposed GOA when compared to other optimization techniques. The GOA exhibits exceptional MPPT tracking characteristics, characterized by rapid tracking speed, heightened efficiency, and minimal oscillations within the PV system. Consequently, the GOA effectively addresses one of the MML issues.
      2  33