As distributed energy resources become more prevalent, rural electrical grids evolve from passive to active configurations. The unpredictability, fluctuation, and variability of these distributed energy sources bring about new uncertainties, risks in rural low-voltage networks. These fluctuations can lead to issues like voltage instability, frequency deviations, and power imbalances, complicating the reliable operation of the grid. Effectively managing these challenges is essential to maintaining grid stability while promoting the adoption of renewable energy in rural areas. This article introduces a micro energy storage optimization model tailored for rural low-voltage distribution networks, aimed at mitigating load rate fluctuations in distribution transformers and enhancing voltage quality amidst the integration of distributed power sources in these areas. This approach uses the positioning and size of the energy storage system as variables for optimization, focusing on minimizing the impact of load rate variations on distribution transformers, ensuring voltage standards are met, and maximizing the efficiency of the micro energy storage system's capacity. The study introduces a sophisticated multi-objective particle swarm optimization technique, adjusting the inertia weight dynamically in response to the distance between each particle and the particle deemed to be the global best. The information entropy method is employed to assign weights to each objective value. The model underwent evaluation on a streamlined rural distribution network specific to a certain area. The results reveal that incorporating a micro energy storage system within the distribution area significantly reduces the variability in transformer load levels caused by distributed power sources. Concurrently, this integration improves the adherence to voltage standards within the rural distribution networks.