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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pzh7fcnla5d4ni6s4eqgv7uk5e" style="color: black;">Emerging Science Journal</a>
This paper proposes distribution network optimization with scattered generator integration using the immune-clonal selection (ICS) method. Nowadays, the high popularity of scattered generators (SG) has made distribution networks essential to manage appropriately. This interest is because SG is usually injected into the distribution network due to the ease of accessing the network and the voltage level of the distribution network, which is easier for SG to reach. However, the presence of SG as a<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.28991/esj-2021-01312">doi:10.28991/esj-2021-01312</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2vi2d4libbhphmf2h5tjho5a3q">fatcat:2vi2d4libbhphmf2h5tjho5a3q</a> </span>
more »... distribution network is increasingly dynamic, so that appropriate techniques are needed to achieve adequate network performance through network optimization. The ICS method is expected to be the right solution for this task. The ICS technique was chosen for its excellence in accurately optimizing for multi-objectives while avoiding premature convergence to local minima. The ICS approach was applied to IEEE model distribution networks of 33-bus and 71-bus. The optimization results show that the effectiveness and superiority of the ICS method, which is indicated by shallow power losses with a better voltage profile, and the load balance on each feeder is maintained. Doi: 10.28991/esj-2021-01312 Full Text: PDF
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