Muhammad Irwanto Misrun
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Preferred name
Muhammad Irwanto Misrun
Official Name
Muhammad Irwanto, Misrun
Alternative Name
Irwanto, Muhammad
Irwanto, M.
Misrun, Muhammad Irwanto
Irwanto, Muhamad
Misrun, M. I.
Main Affiliation
Scopus Author ID
57199152380
Researcher ID
DHD-5414-2022

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  • Publication
    Analysis on the Effect of DC Current Changes on the Magnetic Field of Wireless Power Transfer
    ( 2023-01-01)
    Muhammad Irwanto Misrun
    ;
    Ali M.B.
    ;
    Nugraha Y.T.
    ;
    Baharuddin Ismail
    ;
    Nisja I.
    ;
    Leow Wai Zhe
    The generation of electromagnetic radiation in a solenoid, driven by alternating current (AC) voltage, is directly influenced by the voltage and current flowing through the solenoid. Exploiting this concept, wireless power transfer (WPT) systems can be developed. These systems consist of a sending coil and a receiving coil, both equipped with solenoids. The sending coil is connected to a half bridge circuit to generate AC voltage, which is then transmitted to the receiver coil. In this study, the effects of various factors on the performance of the wireless power transfer system were investigated, with a particular focus on the impact of DC voltage and input DC current. To examine these effects, an experimental setup was employed where the transmitter and receiver coils were powered by a DC voltage source. By varying the voltage and current parameters, the study aimed to analyze their influence on the wireless power transfer process. The simulation results show that 100 V and 150 V of DC current will produce 36.54 A and 54.8 A of input DC current respectively with constant resistor 7.54×10-2 Ω. The result shows that the input DC current is directly proportional with the magnetic field, AC current at sending and receiving coil, voltage at sending and receiving coil and AC power at receiving coil. Increasing the input DC current will increase the magnetic field, AC current at sending coil and receiver coil, voltage at transmitter coil and receiving coil and AC power at receiving coil and vice versa.
  • 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.
  • Publication
    Development A Portable Solar Energy Measurement System
    ( 2021-07-26)
    Atika Z.
    ;
    Leow Wai Zhe
    ;
    Iszaidy I.
    ;
    Mohd Irwan Yusoff
    ;
    Safwati Ibrahim
    ;
    Muhammad Irwanto Misrun
    ;
    Wafi N.M.
    ;
    Saw S.X.
    This project presents the design and development a portable measurement device for measure and monitor solar panel parameters by using Internet of Things (IoT) concept. Solar energy measurement plays a very important role in the measurement of parameter reading for the determination of output generated, but the challenge is only performed manually at the work site using a clamp meter or a multimeter. Furthermore, it was very difficult to get the value at that time, and the data recovery error occurred. There are three specific objectives have been used for the project. Firstly, the relevant circuits for this project are design and built the circuit by using software. The output of the measurement solar irradiance, ambient temperature, solar panel temperature, current and voltage value were displayed on LCD. Next, IoT concept is used for solar panel measurement and monitoring. The value of the measurement and monitoring is used ThingSpeak cloud and ThingView application on the smartphone. It can be collected the portable solar for the energy measurement system can monitor on site, anywhere and anytime using IoT platform.
      20  1
  • Publication
    Performance power evaluation of DC fan cooling system for PV panel by using ANSYS CFX
    ( 2017-09-26)
    Nur Syafiqah Zhubir
    ;
    Nasrul Amri Mohd Amin
    ;
    Mohd Irwan Yusoff
    ;
    Muhammad Irwanto Misrun
    ;
    Leow Wai Zhe
    ;
    Amelia A.R.
    A research has been conducted to find the optimum combination for DC fan air cooling system of photovoltaic (PV) panel. During normal operation of PV panel, it is estimated that only 15 % of solar radiation is converted into electrical energy. Meanwhile, the rest of the solar radiation is converted into heat energy which affects the performance of the PV panel. Therefore, the aim of this research is to investigate the performance power evaluation of DC fan cooling system for PV panel by using ANSYS CFX. The effect of airflow configuration of DC fan has been investigated. This is to analyze whether the airflow circulation of DC fan cause a change towards the maximum temperature of PV panel. Besides, the impact of varying number of DC fans attached at the back of PV panel is evaluated. The result of airflow circulation of DC fan has been discussed. Meanwhile, with the increment number of DC fans, the PV panel temperature drops significantly. As a conclusion, the optimum number of DC fans is two with the combination of inlet airflow.
      1  23
  • Publication
    Assessment of wind power potential in the North region of Malaysia, Chuping Perlis
    ( 2023-01-01)
    Thiraphorn B.L.
    ;
    Leow Wai Zhe
    ;
    Safwati Ibrahim
    ;
    Irwan Y.M.
    ;
    Muhammad Irwanto Misrun
    ;
    Tan X.J.
    ;
    Ananda-Rao K.
    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.
      17  2