A Novel Artificial Rabbits Optimization Algorithm for Optimal Location and Sizing of Multiple Distributed Generation in Radial Distribution Systems

The major challenges of the distribution system are optimal location and sizing of distributed generation (OLSDG), as these significantly influence the system losses, voltage profile and voltage stability issues. In this paper, the OLSDG problem is solved by a newly developed artificial rabbits optimization (ARO) algorithm. The objective of an OLSDG problem is to minimize real power loss and total voltage deviation (TVD) and enhance the voltage stability index (VSI) in radial distribution systems (RDSs) while satisfying all the constraints. The effectiveness of the ARO has been validated on IEEE 33-bus and large-scale 118-bus RDSs for various power factors of distributed generation (DG), like optimal power factor (OPF), fixed power factor, and unity power factor (UPF) under four different scenarios. It has been found that RDSs' performance in terms of TVD, VSI, and mainly power loss is much improved when DGs have been operated with an OPF. In the case of DGs operating with UPF, the power loss decreases by 65.50% and 60.24% in an IEEE-33 bus and 118-bus RDSs, respectively, whereas DGs operating with OPF, the power loss reduces to 94.44% and 90.28%, respectively. The results obtained by ARO are validated by comparing them with the results of other optimization methods in the recent literature. The results prove that the proposed ARO is more efficient, has less computational time and can provide better solutions for an OLSDG problem.