Abstract:[Objective] To address the issues of voltage fluctuations and increased network losses in distribution network caused by high photovoltaic penetration, this paper proposes an optimal configuration strategy of energy storage power source based on time-series comprehensive voltage-active power sensitivity. [Methods] Firstly, a static comprehensive sensitivity matrix between nodal voltage and active power variation was established to quantify the impact of power injection on voltage deviation across all nodes. Then, to reflect the time-series characteristics of photovoltaic output and load fluctuation, a time-series weighting factor was introduced to correct the influence of voltage deviations at different time periods, thereby forming a time-series comprehensive sensitivity index that determined the priority of energy storage system installation locations. On this basis, a multi-objective optimization model was formulated that simultaneously minimized the comprehensive operating costs of the energy storage system, voltage deviation of the distribution network, and total network losses. Subsequently, the optimization model was solved using an improved particle swarm optimization algorithm, which enhanced convergence speed and avoided local optimal by dynamically adjusting inertia weight and learning factors. Finally, generative adversarial network was employed to generate diverse distribution network operational scenarios, thereby enriching the optimization dataset and improving the robustness of solutions under photovoltaic and load uncertainty. [Results] The case study results demonstrated that, compared with conventional voltage sensitivity analysis method, the proposed time-series sensitivity analysis method effectively enhanced the precision and targeted nature of node voltage regulation. The optimized energy storage system configuration achieved collaborative improvement in both economic performance and renewable energy utilization capability while ensuring that nodal voltages remained within permissible limits. [Conclusion] The proposed strategy significantly accelerates the energy storage planning process of distribution network, enhances its ability to maintain voltage stability under photovoltaic fluctuations, and promotes the economic and reliable operation of distribution network with high proportion photovoltaic.