<p>Developing countries face increasing pressure to balance rising energy demands with the pursuit of sustainable development. This study addresses this challenge by evaluating renewable energy projects using a group decision-making framework that integrates technical, economic, environmental, and social dimensions. To handle incomplete information, expert opinion ambiguity, and inherent variability, a novel dual spherical fuzzy rough number cloud-based approach is proposed. This approach combines spherical fuzzy rough numbers with a probabilistic cloud model, enhancing the representation of uncertainty by capturing both ambiguity and randomness in expert evaluations. The main contributions include introducing this advanced uncertainty-handling approach and developing a hybrid decision-making framework that enhances the reliability and robustness of renewable energy project assessments, supported by real-world validation. An extended entropy-based method is used to determine the weights of evaluation criteria, while a unified utility function integrates the strengths of weighted sum and weighted product methods to rank alternatives. A case study on renewable energy projects in Iran demonstrates the model’s applicability. The results show that solar energy is the most viable renewable option. Validation and sensitivity analyses confirm the robustness of these findings.</p>