Siti Rafidah Abdul Rahim
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Preferred name
Siti Rafidah Abdul Rahim
Official Name
Siti Rafidah, Abdul Rahim
Alternative Name
Abdul Rahim, Siti Rafidah
Rahim, S. R.
Rahim, S.R.A
Abdul Rahim, S.R.
Rahim, S.R. Abd
Main Affiliation
Scopus Author ID
11639107900
Researcher ID
E-5412-2011

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  • Publication
    A hybrid multi-objective Evolutionary Programming-Firefly Algorithm for different type of Distributed Generation in distribution system
    ( 2022-12-01)
    Noor Najwa Husnaini Mohammad Husni
    ;
    Siti Rafidah Abdul Rahim
    ;
    Mohd Rafi Adzman
    ;
    Hussain M.H.
    ;
    Musirin I.
    ;
    Syahrul Ashikin Azmi
    With the rise in electricity demand, various additional sources of generation, known as Distributed Generation (DG), have been introduced to boost the performance of power systems. A hybrid multi-objective Evolutionary Programming-Firefly Algorithm (MOEPFA) technique is presented in this study for solving multi-objective power system problems which are minimizing total active and reactive power losses and improving voltage profile while considering the cost of energy losses. This MOEPFA is developed by embedding Firefly Algorithm (FA) features into the conventional EP method. The analysis in this study considered DG with 4 different scenarios. Scenario 1 is the base case or without DG, scenario 2 is for DG with injected active power, scenario 3 is for DG injected with reactive power only and scenario 4 is for DG injected with both active and reactive power. The IEEE 69-bus test system is applied to validate the suggested technique.
  • 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.
      28  3
  • 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.
      31  3
  • Publication
    Cost of energy losses analysis using a hybrid evolutionary programming-firefly algorithm for distributed generation installation
    ( 2022)
    Noor Najwa Husnaini Mohammad Husni
    ;
    Siti Rafidah Abdul Rahim
    ;
    Mohd Rafi Adzman
    ;
    Muhammad Hatta Hussain
    ;
    Ismail Musirin
    This paper presents the Hybrid Evolutionary Programming-Firefly Algorithm (EPFA) technique for the cost of energy losses analysis of distributed generation (DG). In this study, EPFA is developed to determine the optimal size of DG while considering the system’s energy losses. EPFA is developed based on embedded Firefly Algorithm (FA) properties into the classical EP technique. The objective of this study was to reduce the cost of energy losses while increasing the voltage profile and minimizing distribution system losses between the different operational strategies and types of DG. In this study, the analysis was done by considering DG type 1 and DG type 2. The proposed technique was tested using the IEEE 69-bus test system. In terms of economic concerns, power system planners can use the information acquired for utility planning to determine the right location and capacity of DG. Finally, the proposed method can determine the appropriate DG sizing while reducing the cost of energy losses and total losses in the system, based on the simulation results.
      3  3