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Research background: Over the last ten years, a substantial amount of scholarly research has delved into energy communities (ECs) from diverse viewpoints. These ECs are extremely important in setting the pathway to a clean energy transition. Purpose of the article: Our objective is to glean valuable insights from publications indexed in the Web of Science (WoS) database to deepen our comprehension of ECs and their academic discourse. Methods: Data analytics, factorial analysis, and more complex natural language processing (NLP) techniques such as latent Dirichlet allocation (LDA) are implemented to extract valuable insights from over 1000 WoS publications relevant in the EC field. The primary contribution of this study lies in furnishing details regarding the key contributors to the EC scholarly landscape, including authors, their affiliations, universities, and countries of origin. Additionally, we aim to elucidate the prevalent keywords and thematic approaches employed in their research endeavors. Findings & value added: Considering the extracted dataset, an annual growth rate of 21.15% has been recorded, highlighting the research community’s interest in the field of ECs. Furthermore, three topics are optimally obtained. Overall, a coherence score of 0.44 suggests that the LDA model performs adequately in terms of topic interpretation. Topic 1 relates to community-based energy initiatives. Topic 2, featuring terms like “grid,” “study” and “EU” alongside “energy” and “community,” suggests a focus on energy systems. Topic 3 includes terms such as “generation,” “analysis” and “consumption,” indicating a topic that is centered around the technical or analytical aspects of energy production and usage. This study underscores how the alignment between state laws and EU directives in supporting ECs can serve as a model for other regions. The findings suggest that similar policy frameworks could be effectively adapted to different national contexts, providing valuable insights for countries looking to enhance their renewable energy strategies.
Delcea et al. (Mon,) studied this question.