Hydrogen energy storage technology selection through a cutting-edge probabilistic linguistic decision framework

Abstract

As a viable alternative to traditional energy forms, hydrogen energy proves effective owing to its feasible cost and reduced pollution. The storage of such a renewable energy source is essential for ensuring energy security and promoting sustainability. However, earlier studies on energy storage technology (EST) selection cannot handle complex linguistic expressions and hesitation during the decision process. Motivated by the issue, a probabilistic linguistic decision approach is developed in the present study to model linguistic expressions in daily conversations effectively. Besides, a new integrated approach is introduced by considering the regret factor for expert weight determination, weighted Cronbach’s approach for criteria weight determination, and a novel ranking procedure with a weighted approximation for prioritizing ESTs. A case example is exemplified by considering nine criteria and six ESTs to clarify the usefulness and practicality of the proposed framework. The main novelty/benefits of the study are: (i) handle uncertainty better; (ii) capture interrelationship among criteria; (iii) reduce bias by methodically determining the importance of experts; and (iv) provide a personalized ranking of ESTs. Findings depict that total cost is the foremost driver for hydrogen EST selection, while pressure cylinder storage is the most viable technology. Finally, the benefits and usefulness of the study are realized through sensitivity and comparison analyses. This study can guide and assist energy officials, academicians, governments, and other stakeholders facing hydrogen EST selection issues.