Muhamad Hatta Hussain
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Preferred name
Muhamad Hatta Hussain
Official Name
Muhamad Hatta , Hussain
Alternative Name
Hussain, Muhammad Hatta
Hussain, Muhamad Hatta
Hussain, M. H.
Main Affiliation
Scopus Author ID
36559434400
Researcher ID
DTG-2216-2022

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  • Publication
    Optimal Allocation and Sizing of Multi DG Units including Different Load Model Using Evolutionary Programming
    ( 2021-06-11)
    Mohd Fayzul Mohammed
    ;
    Siti Rafidah Abdul Rahim
    ;
    Azralmukmin Azmi
    ;
    Wan Zulmajdi Wan Zanudin
    ;
    Muhamad Hatta Hussain
    ;
    Nurul Huda Hashim
    ;
    Aliman O.
    This paper presents the optimal allocation and sizing of multi distributed generation (DG) units including different load models using evolutionary programming (EP) in solving power system optimization problem. This paper also studies on the effect of multi DG placement in different load model. To optimize the power distribution system, multi DG units were used to reduce losses power distribution system. By using EP, the optimal allocation and sizing of multi-DG was determined in order to obtain maximum benefits from its installation. The propose technique was tested into IEEE 69-bus distribution system. The result shows the placement of DG can reduce power loss 89% to 98%. The placement of multi-DG unit has better performance compare to single DG.
      1
  • Publication
    Optimal distributed generation for loss minimization using Sand Cat Swarm Optimization
    ( 2024-04-15)
    Adnan A.A.S.M.
    ;
    Muhamad Hatta Hussain
    ;
    Siti Rafidah Abdul Rahim
    ;
    Azralmukmin Azmi
    ;
    Musirin I.
    ;
    Mohamad Nur Khairul Hafizi Rohani
    ;
    Nurul Huda Hashim
    ;
    Radziyan J.A.
    Integration of Distributed Generation (DG) into the transmission system is the current paradigm for creating unique transmission grids. Grid line loss and voltage quality may suffer from unreasonably configured DG. The aim of this paper is to rationally allocate distributed generators (DGs) in the transmission network to reduce power losses and guarantee a safe and reliable power supply to the loads. The works suggests an optimal distributed generation using Sand Cat Swarm Optimization (SCSO) for loss minimization to reduce power loss while enhancing voltage stability. The proposed algorithm was simulated and evaluated using the Matrices Laboratory (MATLAB) script programming language and has been implemented on IEEE 14-bus transmission system. The results exhibit that the SCSO method is able to determine the optimal DG size and reducing total losses by 40.77 percent for DG type 1 as compared with Particle Swarm Optimization (PSO) algorithm, 38.98% at bus 10. It can be revealed that SCSO can be used by power system planners to choose the best sizing and location.
      1