Leow Wai Zhe
Thumbnail Image
Preferred name
Leow Wai Zhe
Official Name
Wai Zhe, Leow
Alternative Name
Leow, Wai Zhe
Leow, W. Z.
Zhe, Leow Wai
Zhe, L. W.
Main Affiliation
Scopus Author ID
56178375200
Researcher ID
DXJ-9302-2022

Research Output
Now showing 1 - 4 of 4
  • Publication
    MPPT charge controller using fuzzy logic for battery integrated with solar photovoltaic system
    (Semarak Ilmu Publishing, 2025-05)
    Kumuthawathe Ananda-Rao
    ;
    Afifah Shuhada Rosmi
    ;
    Steven Taniselass
    ;
    Nor Hanisah Baharudin
    ;
    Leow Wai Zhe
    In comparison to other Renewable Energy (RE) resources, solar energy has become the most prominent and prospective source for generating electricity, substituting conventional sources. However, solar Photovoltaic (PV) energy production is dependent on solar irradiance and cell temperature. By implementing the Maximum Power Point Tracking (MPPT) algorithm, it is achievable to maximize the power from solar PV. In spite of this, there is still a slower convergence rate, a significant fluctuation around Maximum Power Point (MPP), and a drift issue caused by rapid irradiance variations in solar PV. In order to prevent oscillation and attain a steady state and continuous output of the PV module, a Fuzzy Logic (FL)-based MPPT has been designed in this work. With the buck converter as the DC-DC converter and the lead acid battery as the input, the Perturb & Observe (P&O) MPPT method is selected. The overall design will be developed using Matlab Simulink, and the efficiency of the FL-MPPT charge controller will be evaluated under constant and step irradiance. Additionally, the battery's State of Charge (SOC) will be monitored to prevent overcharging and discharge. In addition, the effectiveness of the controller will be evaluated with and without the MPPT method. On the basis of simulation results obtained from constant and step irradiance levels, the FL-MPPT charge controller with the P&O algorithm and the lead acid battery as the load was able to maintain maximum system efficiency while extending battery life. The FL-MPPT charge controller obtained about 96% efficiency for both irradiance profiles, whereas the system without the FL-MPPT algorithm only achieved 42% efficiency.
  • Publication
    A Potential Controller for Smart Electrical Energy Management System
    ( 2021-06-11)
    Kumuthawathe Ananda-Rao
    ;
    Mohd Alif Ismail
    ;
    Afifah Shuhada Rosmi
    ;
    Leow Wai Zhe
    ;
    Surina Mat Suboh
    ;
    Muhammad Izuan Fahmi Romli
    ;
    Abdullah A.M.
    Integrated energy utilization has been recognized as a productive way towards better energy management, besides increasing Renewable Energy (RE) penetration. Thus, the combination of RE integrated with the Battery Energy Storage System (BESS) has been recognized as the primary solution where it is necessary to have a controller to interface the system efficiently. Hence, a smart electrical energy management system controller is designed and developed based on load leveling and peak shaving applications for real-time AC power management in this work. The main function of the controller is to continuously monitor and maintain the load demand and to produce a leveled or shaved load profile that will be seen at the grid network by controlling the battery operation. The testing results concluded that the controller able to perform both the energy applications. Overall, a dual function controller based on energy applications to maintain consumer load demand usage more securely and reliably, so that the utility bill is reduced and the battery lifetime is prolonged simultaneously is achieved in this work.
      9  31
  • Publication
    Assessment of wind power potential in the North region of Malaysia, Chuping Perlis
    ( 2023-01-01)
    Thiraphorn Bun Leew
    ;
    Leow Wai Zhe
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Tan Xiao Jian
    ;
    Muhammad Irwanto Misrun
    ;
    Kumuthawathe Ananda-Rao
    The wind turbines is a main device that convert the kinetic energy from blades to electrical energy. Before installing wind turbines, the Weibull probability distribution must be calculated to determine the certain wind speed probability. Many problems will come if there no analysis the characteristics of wind in selected location, such as wind speed that not suitable for building wind farm to supply the population in that area. Shape and scale factors, which be controlled in a variety of ways, influence the Weibull distribution. Many studies have looked into which of the various Weibull parameter estimation methods is the most dependable. However, because the results of these investigations were inconsistent, research into more trustworthy Weibull parameter estimation methods is still ongoing. An analysis of data collected Chuping, Perlis for two years was conducted in this study (from 2018 to 2019). By using statistical analysis to evaluate the Weibull distribution method, this study used three methods to compared the Weibull parameters and identified the most reliable and effective method to obtain the Weibull probability distribution by using a three approach that compares the variances of RMSE, MSE and R2, which provides comprehensive insight into level error and volatility. Modified maximum likelihood method, graphical method, and power density method are the three methods used in this study. Therefore, the graphical method has the best accuracy in the wind speed distribution prediction, several methods such as the modified maximum likelihood method, and the power density method have the worst prediction of the wind speed distribution based on all the statistical method variances for this region.
      7  29
  • Publication
    Comparative Study of Three Methods for Determining Weibull Parameters in Pauh Putra, Perlis
    ( 2021-06-11)
    Thiraphorn B.L.
    ;
    Leow Wai Zhe
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Muhammad Irwanto Misrun
    ;
    Kumuthawathe Ananda-Rao
    ;
    Amelia A.R.
    This paper studied about analysis characteristics of wind speed at Pauh Putra, Perlis, where nearest to Chuping station, Perlis, Malaysia. The wind speed characteristics consist of monthly and annual wind speed in Perlis, Malaysia. By using Weibull distribution, three different methods to calculate the potential of wind power generation and analysis the characteristics of wind speed at Pauh Putra, Perlis. The results present the means wind speed is 1.0790 m/s and 1.1321 m/s for 2018 and 2019, respectively. The highest monthly mean wind speed occurred in February for both years, 2018 and 2019. Besides, the lowest monthly wind speed for 2018 in May and for 2019 in October. The Weibull distribution summarized the highest probability density is 120% in the wind speed, 1.1 m/s using the Maximum Likelihood Method (MLM) method for these two years. Furthermore, this research found that the Energy Pattern Factor (EPF) Method is stretched to the right, and its height decreased from other methods for both years based on the graph of the wind speed of probability density function. The Maximum Likelihood Method (MLM) for these two years is higher because its shape parameters are relatively higher based on the graph of the wind speed of probability density function.
      33  1