This article proposed a new model for reconfiguration and distributed generation (DG) allocation in the distribution network by considering network loss reduction and power quality improvement. The objective function aims to minimize losses and improve power quality indices by using the new antlion optimizer (ALO) algorithm. The proposed reconfiguration has been investigated on an unbalanced IEEE 33-bus grid with and without DG resources and capacitors. In this study, a branch exchange technique with an optimization method is used to determine the best network arrangement. Simulation results are implemented in different scenarios. In each of the scenarios, power quality indices and network losses before and after the optimization are compared. The results indicate that by using the proposed method, the rate of power quality indices and the losses in the case study are reduced. Also, the results of this study were compared with the results of sample studies. The results show that ALO has better performance with the goal of power loss reduction.

In this paper, a methodology of sizing optimization of a stand-alone hybrid PV/wind/battery power generation system (HPWGS) is proposed. The main objective of this optimization is to minimize the total annual cost (TAC) of the hybrid system considering power balanced constraint and determination of the optimal number of wind turbines, PV panels, and batteries. For this purpose, a new meta-heuristic nature-inspired algorithm, called Grey Wolf Optimizer is utilized. The obtained results show that the proposed methodology finds optimal sizing of the HPWGS easily with fast convergence and lower cost. Comparing the results of this new method with the well-known published works in the literature, the superior capabilities of this proposed method are demonstrated. Moreover, the results show that the reliability characteristics are weakened with decreasing the component availability, and the supply reliability of the HPWGS is improved by increasing the inverter efficiency while the TAC is decreased. Furthermore, the HPWGS can cover the load demand variations with high reliability.