The aim of the study is to review XAI studies in terms of their solutions, applications and challenges in renewable energy and resources. The results have shown that XAI really helps to explain how the decisions are made by AI models, to increase confidence and trust to the models, to make decision mode reliable, show the transparency of decision-making mechanism. Even if there have been a number of solutions such as SHAP, LIME, ELI5, DeepLIFT, Rule Based Approach of XAI methods, a number of problems in metrics, evaluations, performance and explanations are still specific, and require domain experts to develop new models or to apply available techniques. It is hoped that this article might help researchers to develop XAI solutions in their energy applications and improve their AI approaches for further studies.