Mohd Rafi Adzman
Thumbnail Image
Preferred name
Mohd Rafi Adzman
Official Name
Mohd Rafi , Adzman
Alternative Name
Adzman, M. R.
Adzman, Mohd Rafi Bin
Adzman, Mohd Rafi
Main Affiliation
Scopus Author ID
16833392100
Researcher ID
AAF-8313-2019
F-8971-2017

Research Output

Filters

2
2
Reset filters

Settings
Now showing 1 - 2 of 2
  • Publication
    Cost of Energy Losses for Distributed Generation Using Hybrid Evolutionary Programming-Firefly Algorithm
    ( 2021-12-01)
    Noor Najwa Husnaini Mohammad Husni
    ;
    Siti Rafidah Abdul Rahim
    ;
    Mohd Rafi Adzman
    ;
    Muhamad Hatta Hussain
    ;
    Musirin I.
    The cost of energy losses analysis for distributed generation (DG) is presented in this paper using a Hybrid Evolutionary Programming-Firefly Algorithm (EPFA). The proposed method was created to determine the optimal DG sizing in the distribution system while accounting for the system's energy losses. This study presents an investigation into hybrid optimization techniques for DG capabilities and optimal operating strategies in distribution systems. The objectives of this study were to reduce the cost of energy losses while increasing the voltage profile and minimize distribution system losses. In this study, the analysis was done by consider DG type I which is DG-PV. The suggested methodology was tested using the IEEE 69-bus test system, and the simulation was written in the MATLAB programming language. Power system planners can use appropriate location and sizing from the results obtained for utility planning in terms of economic considerations. From the simulation, the result shows the proposed method can identify the suitable sizing of DG while reduce cost of energy losses and total losses in the system.
  • Publication
    A Hybrid Optimization Approach for Power Loss Reduction and Voltage Profile Improvement in Distribution System
    ( 2022-01-01)
    Noor Najwa Husnaini Mohammad Husni
    ;
    Siti Rafidah Abdul Rahim
    ;
    Mohd Rafi Adzman
    In the past decades, the electrical power system is designed and developed to satisfy the owner demand that continuously appears in many variations. Hence, engineers have put their full effort to solve the problem associated with electrical power systems that come and might arise in the future. Therefore, distributed generation (DG) has been introduced to solve multiple electrical power system problems. The proposed methodology presented in this study focuses on minimizing network power losses, improving the voltage profile of system operation, and security constraints in a distribution. It is known that the location and capacity of DG play significant roles in the system losses in a distribution system. A hybrid metaheuristic nature-inspired algorithm is presented in this study for optimal location and sizing of multiple DG units. The best location and optimal sizing of DGs will be determined through Hybrid metaheuristic of Artificial Immune System Firefly Algorithm (AISFA). The designated technique will be tested into IEEE-69 test system using MATLAB software. For reducing the power losses, the simulation results have shown that bus 61 is the best location for reducing power losses and improving voltage profile in IEEE-69 test system in the preliminary result. By installing DG at bus 61, the real power losses improve about 89%, with a voltage profile improvement index up to 1.249099.