Ant Colony Optimization for the Optimal Placement of Lithium-Ion Battery Energy Storage Systems in Electrical Distribution Networks

This study presents an Ant Colony Optimization (ACO)-based methodology for the optimal placement of lithium-ion battery energy storage systems (BESSs) in radial electrical distribution networks. The proposed framework integrates base-case power-flow assessment, critical-bus identification, discrete BESS siting, technical–economic objective evaluation, and post-optimization validation. The methodology is applied to the IEEE 33-bus radial distribution test system, where the initial operating condition is characterized in terms of nodal voltage profile, voltage deviation, voltage-stability index, active-power losses, and annual loss cost. The optimization process identifies buses 13 and 31 as the most suitable locations for two identical BESS units, with the reported validation case evaluating each unit at upper admissible capacity limits of 1000kW and 4000kWh. The obtained results show that the optimized BESS allocation increases the minimum voltage profile to values above 0.94p.u., raises the voltage-stability index to more than 0.88, reduces active-power losses to approximately 0.0166p.u., and decreases the annual cost associated with active-power losses by more than 66% relative to the base case. Additional validation through sensitivity analysis, repeated stochastic runs, operating-mode evaluation, and comparison against a genetic algorithm confirms the consistency and robustness of the proposed ACO-based methodology. The results demonstrate that the proposed framework provides a technically consistent and computationally accessible solution for improving voltage regulation, reducing feeder losses, and lowering loss-related operating costs in radial distribution systems.