Browsing by Author "Ali, S"

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    OPTIMAL INTEGRATION OF DISTRIBUTED GENERATION IN RADIAL DISTRIBUTION SYSTEM USING PARTICLE SWARM OPTIMIZATION TECHNIQUE
    (university of el oued/جامعة الوادي, 2018-09-01) Kumar, M; Das, B; Ali, S; Nallagownden, P; Elamvazuthi, I
    Fossil fuel depletion, electricity demand increment, and environmental degradation shift the power system network to adopt distributed generation (DG) at local distribution system. The optimal integration of distributed generation witnesses many benefits such as reduce power losses, increase voltage profile and stability of the system etc. However, the non-optimal integration may deteriorate the existing operation. Therefore, this paper presents the methodology to optimally integrate the distributed generation in the radial distribution system. The main aim is to reduce the power losses and improve the voltage profile using particle swarm optimization technique. The proposed technique is implied on benchmark IEEE 69 bus system. The proposed technique is also compared with many optimization algorithms. The overall results show that the proposed method gives better results as compared to other literature algorithms
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    OPTIMAL INTEGRATION OF DISTRIBUTED GENERATION IN RADIAL DISTRIBUTION SYSTEM USING PARTICLE SWARM OPTIMIZATION TECHNIQUE
    (university of el oued/جامعة الوادي, 2018-09-01) Kumar, M; Das, B; Ali, S; Nallagownden, P
    Fossil fuel depletion, electricity demand increment, and environmental degradation shift the power system network to adopt distributed generation (DG) at local distribution system. The optimal integration of distributed generation witnesses many benefits such as reduce power losses, increase voltage profile and stability of the system etc. However, the non-optimal integration may deteriorate the existing operation. Therefore, this paper presents the methodology to optimally integrate the distributed generation in the radial distribution system. The main aim is to reduce the power losses and improve the voltage profile using particle swarm optimization technique. The proposed technique is implied on benchmark IEEE 69 bus system. The proposed technique is also compared with many optimization algorithms. The overall results show that the proposed method gives better results as compared to other literature algorithms.