Optimal allocation of multi-objective distributed energy storage capacity

To tackle the optimal allocation of distributed energy storage systems, this work proposes a multi-objective optimization model aligned with the configuration process, focusing on strategic placement and capacity determination. Its objective function comprehensively considers the energy storage cost, voltage offset, network loss analysis, load fluctuation and other indicators, and weights each optimization index, and selects the gray wolf algorithm with fast optimization speed and high optimization accuracy to solve it. Finally, the case study employs a forward-backward power flow algorithm to address the optimization problem, followed by a systematic comparison of operational metrics pre- and post-distributed energy storage integration. It is verified that the energy storage configuration model has the optimization effect on a number of indicators in the regional power grid, in which the voltage fluctuation is reduced by $7.36 \%$, the network loss is reduced by $4.27 \%$, and the load fluctuation is reduced by $\mathbf{2 2. 7 4 \%}$.