MULTI-OBJECTIVE OPTIMAL CAPACITY AND PLACEMENT OF DISTRIBUTED GENERATORS IN THE POWER SYSTEM NETWORKS USING ATOM SEARCH OPTIMIZATION METHOD

Nowadays, renewable energy sources become a significant source of energy in the new millennium. The continuous penetration of dispersed resources of the reactive power into power systems is predicted to introduce new challenges. Power loss mitigation and voltage profile development are the major investigation challenges that recently attracted the attention of researchers in the field of power systems. Distributed generation (DG) is widely preferred because it is a highly effective solution that strengthens the performance of power system networks. This multiobjective function study aims to minimise power losses in the feeders, sustain voltage levels and reduce the application cost of DGs by adapting the atom search optimisation simulated on MATLAB software. Two different IEEE power test systems, namely, a 33 bus radial distribution system (RDS) and a 14-bus power system that hosts 1, 2 and 3 DGs in both systems, are demonstrated in this research. Correspondingly, backward–forward sweep and Newton–Raphson power flow methods are used for each system. The proposed technique is compared with the genetic algorithm particle swarm optimisation (GA-PSO) method. Results depict the effectiveness of the proposed method in minimising system power losses and in regulating the voltage profile where the power loss reduction is 25.38% in the 33 bus RDS using 2 DGs. By contrast, the power loss reduction percentages in the 14 bus system are 0.316% and 0.169% in systems with 1 and 2 DGs, respectively. The voltage profile has been enhanced compared with those in the original case and the results obtained from the GA-PSO method