Azralmukmin Azmi
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Preferred name
Azralmukmin Azmi
Official Name
Azralmukmin, Azmi
Alternative Name
Azmi, Azralmukmin
Azmi, A.
Azmi, Azralmuknin
Main Affiliation
Scopus Author ID
39360914400
Researcher ID
R-1532-2019

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  • 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.
  • Publication
    Modeling, experimental investigation and real-time control of active water cooling system for photovoltaic module
    ( 2024-01-01)
    Mohamad Shukor Abdul Rahim
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Mohd Sazli Saad
    ;
    Hasanuzzaman M.
    ;
    Azralmukmin Azmi
    ;
    Mohd Fayzul Mohammed
    Photovoltaic (PV) cells are integral in harnessing solar energy, yet their performance is hindered by excessive heat generation, impacting efficiency and sustainability. Addressing the challenge of efficiency loss in photovoltaic (PV) cells due to overheating, this study focuses on optimizing active water cooling control for PV modules. The aim is to develop a dynamic, sustainable model and integrate a PID controller tuned by Sine Cosine Algorithm (SCA), targeting optimal operating temperatures. This study introduces a dynamic model and a closed-loop control system to manage PV cell temperature, investigating the correlation between water flow and temperature regulation. Experimental data is gathered using a pseudo-random binary sequence (PRBS) as an excitation signal, forming the foundation of an Auto Regressive eXogenous (ARX) model. The closed-loop system incorporates a PID controller and tuned using the Sine Cosine Algorithm (SCA) to optimize performance. The resulting model is rigorously validated through experimental investigation, demonstrating its precision in capturing the system’s dynamics. Moreover, the implementation of a controller-based cooling system substantiates the model’s practical efficacy. The research demonstrates significant improvements when implementing a controller-based water-cooling system for photovoltaic (PV) modules. Compared to the baseline scenario without cooling, the system achieves a 34.5% reduction in average PV temperature (from 59.2°C to 38.9°C) and a 9.46% increase in average power output (from 196.7W to 215.3W). Moreover, this system utilizes only 248.8 liters of water, marking a substantial 64% decrease in water consumption compared to traditional free-flow cooling methods, which use 790.9 liters. The research demonstrates that the controller-based cooling approach is a sustainable option, delivering power output comparable to the free-flow method, yet significantly lowering water consumption. This research signifies a turning point for sustainability, offering an efficient and water-conscious approach for enhancing PV system performance, a crucial step toward a greener and more environmentally responsible energy future.
  • 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
    An Effective Salp Swarm Based MPPT for Photovoltaic Systems under Dynamic and Partial Shading Conditions
    ( 2021-01-01)
    Jamaludin M.N.I.
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Ahmed J.
    ;
    Azralmukmin Azmi
    ;
    Syahrul Ashikin Azmi
    ;
    Nur Hafizah Ghazali
    ;
    Babu T.S.
    ;
    Alhelou H.H.
    This study proposes a duty cycle-based direct search method that capitalizes on a bioinspired optimization algorithm known as the salp swarm algorithm (SSA). The goal is to improve the tracking capability of the maximum power point (MPP) controller for optimum power extraction from a photovoltaic system under dynamic environmental conditions. The performance of the proposed SSA is tested under a transition between uniform irradiances and a transition between partial shading (PS) conditions with a focus on convergence speed, fast and accurate tracking, reduce high initial exploration oscillation, and low steady-state oscillation at MPP. Simulation results demonstrate the superiority of the proposed SSA algorithm in terms of tracking performance. The performance of the SSA method is better than the conventional (hill-climbing) and among other popular metaheuristic methods. Further validation of the SSA performance is conducted via experimental studies involving a DC-DC buck-boost converter driven by TMS320F28335 DSP on the Texas Instruments Experimenter Kit platform. Hardware results show that the proposed SSA method aligns with the simulation in terms of fast-tracking, convergence speed, and satisfactory accuracy under PS and dynamic conditions. The proposed SSA method tracks maximum power with high efficiency through its superficial structures and concepts, as well as its easy implementation. Moreover, the SSA maintains a steady-state oscillation at a minimum level to improve the overall energy yield. It thus compensates for the shortcomings of other existing methods.