%0 Journal Article
%T Optimum Simultaneous Distributed Generation Units Insertion and Distribution Network Reconfiguration Using Salp Swarm Algorithm
%J Engineering and Technology Journal
%I University of Technology-Iraq
%Z 1681-6900
%A .Mashal, Ahmed H
%A AL-Rubayi, Rashid
%A Abd, Mohammed Kdair
%D 2020
%\ 11/01/2020
%V 38
%N 11A
%P 1730-1743
%! Optimum Simultaneous Distributed Generation Units Insertion and Distribution Network Reconfiguration Using Salp Swarm Algorithm
%K Power Losses
%K Salp Swarm Algorithm
%K Network reconfiguration
%K voltage profile (VP)
%K distribution system (DS)
%R 10.30684/etj.v38i11A.1792
%X Contemporary researches offer that most researchers have concentrated on either network reconfiguration or Distributed Generation (DG) units insertion for boosting the performance of the distribution system (DS). However, very few researchers have been studied optimum simultaneous distributed generation units insertion and distribution networks reconfiguration (OSDGIR). In this paper, the stochastic meta-heuristic technique belong to swarm intelligence algorithms is proposed. Salp Swarm Algorithm (SSA) is inspired by the behavior of salps when navigating and foraging in the depth of the ocean. It utilized in solving OSDGIR. The objective function is to reduce power loss and voltage deviation in the Distribution System. The SSA is carried out on two different systems: IEEE 33-bus and local Iraqi radial (AL-Fuhood distribution network). Three cases are implemented; only reconfiguration, only DG units insertion, and OSDGIR. Promising results were obtained, where that power loss reduced by 93.1% and recovery voltage index enhanced by 5.4% for the test system and by 78.77% reduction in power loss and 8.2% improvement in recovery voltage for AL-Fuhood distribution network after applying OSDGIR using SSA. Finally, SSA proved effectiveness after an increase in test system loads by different levels in terms of reduced power loss and voltage deviation comparison with other methods.
%U https://etj.uotechnology.edu.iq/article_169236_88c085f26b322c75e36afd78cba37e70.pdf