<p>This paper proposes a Voltage-Dynamic-Distributionally Robust Co-Planning Framework (VDD-CPF) for the optimal siting and sizing of grid-scale energy storage systems (ESSs) in distribution networks with high levels of renewable uncertainty. The framework employs a second-order cone AC power-flow model, together with the Voltage Collapse Proximity Index (VCPI), which incorporates a Dynamic Thermal Rating (DTR) model to capture weather-variable variations in line ampacity and also accounts for stability margins. Renewable load uncertainties are formulated as distributionally robust chance constraints; thus, the planning decision on ESS is subject to frequent extreme events. Energy storage system (ESS) operation is modeled to account for state-of-charge variations, the ratio of the battery’s charge or discharge (C-rate) limits for demand and supply, and throughput-based degradation to maintain realistic long-term asset behavior. A spatial column-and-bar design is carried out for progressive allocation sites and examination of operational feasibility under multiple scenarios. The methodology is demonstrated through the IEEE-33 bus system using realistic PV and true hour power profiles. The simulation outputs of the VDD-CPF site selection and sizing of ESS show that the distribution operation resilience in terms of the voltage flexibility, thermal rating, and dynamic stability margins have been improved by the methodological inclusion. The findings prompt the need for various approaches to reflect the dynamics of the stability indices, thermal behavior, and uncertainty. It is believed that the methodology will be a useful tool for the short yield and long-dated investment planning.</p>