<![CDATA[The increasing penetration of single-phase distributed generation (DG), particularly rooftop photovoltaic systems, has intensified phase imbalance issues in low-voltage distribution networks (DNs). Although numerous DG allocation methods have been developed to reduce power losses and improve voltage profiles, direct mitigation of feeder asymmetry remains insufficiently addressed. In particular, neutral current circulation and localized inter-phase voltage disparities are often overlooked despite their significant impacts on power quality, equipment loading, and system reliability. To address this limitation, this study proposes a symmetry-oriented multi-objective framework for optimal allocation of single-phase DG units in asymmetric distribution networks. The proposed formulation simultaneously minimizes neutral current magnitude and Differential Phase Voltage Drop (DPVD), enabling direct enhancement of feeder operating balance in both the current and voltage domains. The resulting nonlinear mixed-integer optimization problem is solved using a Multi-Objective Coot Optimization Algorithm (MOCOA), which determines the optimal DG locations, capacities, and phase assignments while satisfying network operating constraints. The effectiveness of the proposed framework is validated using 33-bus and 69-bus unbalanced DNs and compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and NSGA-II. The results demonstrate that MOCOA consistently achieves superior performance in terms of neutral current mitigation, voltage balancing, minimum voltage enhancement, and power-loss reduction. For the 69-bus system, the proposed method reduces neutral current and DPVD by 60.06% and 70.75%, respectively, relative to the base case, while also providing the lowest phase imbalance index among all compared methods. The obtained findings indicate that incorporating feeder symmetry objectives into DG planning can significantly improve the operational performance of asymmetric distribution networks. The proposed framework therefore provides a practical and effective solution for DG integration in future DNs with high penetrations of single-phase renewable generation.]]>
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