%0 Journal Article
%@ 18761100
%A Abdullah, M.A.A.
%A Mohd Saad, N.
%A Abas, M.F.
%A Jaalam, N.
%A Ali, A.
%D 2022
%F scholars:17709
%I Springer Science and Business Media Deutschland GmbH
%J Lecture Notes in Electrical Engineering
%K Distributed power generation; Electric load flow; Location,  reductions; Backward/forward sweep power flow; Distribution generation; Forward sweeps; Load growth; Optimisations; Particle swarm optimization algorithm; Power flows; Powerloss; Radial distribution networks, Particle swarm optimization (PSO)
%P 257-268
%R 10.1007/978-981-16-8690-0₂₄
%T Optimization of Radial Distribution Network with Distributed Generation Using Particle Swarm Optimization Considering Load Growth
%U https://khub.utp.edu.my/scholars/17709/
%V 842
%X This article presents a combination of particle swarm optimization (PSO) algorithm and the backward/forward sweep power flow (BFSPF) approach to determine the optimal bus location and size of distributed generation (DG) in a radial distribution network (RDN) considering the load growth. The analysis of the proposed optimization framework is performed using MATLAB and tested on the 33�bus RDN subject to minimize the power losses. The solutions accomplished through the experiments considering four case studies show significant reductions in the system�s total power loss and improvement in desired bus voltage profiles. With the installation of DG, the percentage of reduction in power loss is 47.38 compared to the system�s power loss without DG. The DG size and location to be installed are determined at the 6th bus location with 2.59 MW. The results show that power losses will increase with the increase in load demand. The findings reveal that load growth does not influence the optimal location of the DG. However, the sizes of DGs need to be revised when considering growth in load conditions. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
%Z cited By 1; Conference of 6th International Conference on Electrical, Control and Computer Engineering, InECCE 2021 ; Conference Date: 23 August 2021 Through 23 August 2021; Conference Code:274719