<p>Global sustainability efforts face critical challenges in integrating renewable energy (RE) due to intermittency issues. Energy storage systems (ESS) can accelerate RE adoption, yet selecting optimal solutions for emerging economies requires sophisticated decision frameworks that look beyond purely technological criteria. Our study thus proposes a methodological framework that addresses those complexities by integrating Z-numbers to model uncertainty in stakeholder judgment, Best Worst Method (BWM) with Decision-Making Trial and Evaluation Laboratory (DEMATEL) for interdependent criteria weighting combined with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for multi-criteria ranking. A comprehensive scenario-driven sensitivity analysis (COMSAM) further tests the robustness of the proposed framework. Unlike traditional approaches, this methodology focuses on societal and external factors such as socio-political and logistical dimensions through the SPELL (Social, Political, Economic, Legal, and Logistical) criteria, which are often overlooked in traditional technical assessments. In the Philippine case study, results show lithium-ion batteries consistently ranking highest, followed by pumped hydro, primarily due to government policy support creating positive spillover effects across evaluation criteria. Flywheel energy storage, by contrast, is the lowest-scoring alternative, largely due to negative perceptions and minimal policy support. Scenario-based sensitivity analysis reveals that hydrogen ranks third in high institutional support environments, while sodium-sulfur batteries outperform hydrogen in scenarios with high market viability but lower institutional support. These shifts highlight how context-specific conditions significantly influence ESS preferences in emerging economies. These findings thus underscore the dynamic nature of ESS selection and highlight key levers such as policy design and stakeholder acceptance. </p>