Nur Hafizah Ghazali
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Nur Hafizah Ghazali
Official Name
Nur Hafizah Ghazali, Ghazali
Alternative Name
Ghazali, Nur Hafizah
Ghazali, N. H.
Ghazali, N.
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Scopus Author ID
36104136600

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  • 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.
      33  5
  • Publication
    A new optimization strategy for wind/diesel/battery hybrid energy system
    ( 2022-01-15)
    Aziz A.S.
    ;
    Mohammad Faridun Naim Tajuddin
    ;
    Hussain M.K.
    ;
    Mohd Rafi Adzman
    ;
    Nur Hafizah Ghazali
    ;
    Ramli M.A.M.
    ;
    Khalil Zidane T.E.
    HOMER software is a powerful tool for modeling and optimization of hybrid energy system (HES). The main two default control strategies in HOMER are load following (LF) and cycle charging (CC) strategies. In these strategies, the decision to use the generator or battery at each time step is made based on the lowest-cost choice. Therefore, these strategies are difficult to be implemented in practice especially in countries with continuous fuel price fluctuations. In this study, a new dispatch strategy based on HOMER-MATLAB Link Controller for an isolated wind/diesel/battery HES is proposed to overcome the limitations of the default HOMER strategies. A detailed technical, economic, and greenhouse gas emission analysis is presented for the system under LF, CC, and the proposed dispatch strategies. Besides offering more realistic optimization, the results show that the proposed strategy offers the best economic and environmental performance with a net present cost of $56473 and annual CO2 emissions of 6838 kg. Furthermore, the sensitivity analysis reveals that the proposed strategy is not affected by the fuel price variation, in opposite to LF, and CC strategies which is affected dramatically by this variation. The findings are of paramount importance towards more realistic and efficient energy management strategies.
      47  2