Energy communities (EnCs) are increasingly promoted as a means to support the decentralisation of energy systems and the integration of renewable energy sources, yet lack popularity and wide adoption. At the same time, demand flexibility is an important mechanism that can support EnCs by bringing additional benefits. Nonetheless, these concepts are often addressed separately or incoherently in policy and research, so the benefits of integrating them remain unclear. This paper aims to bridge these concepts and analyse their interaction. First, it sets the context by analysing legal and policy developments and the research landscape. It presents a systematic literature review of recent peer-reviewed publications, consolidating findings across three thematic areas: benefits and challenges for EnC members and system operators, approaches to enhance flexibility, and enabling factors, such as technical issues and data availability. The paper also outlines suggestions where further research is required to better understand and operationalise demand flexibility at the community level. The review shows that demand flexibility can significantly enhance the economic, environmental, and system-level benefits of EnCs but its integration remains fragmented and uneven. In particular, the complex interactions between internal and external incentives, stakeholder perspectives, technologies, and data availability are still insufficiently explored.

Energy communities (EnCs) are emerging as a key mechanism for integrating distributed renewable energy resources and enhancing demand-side flexibility. Selecting appropriate modelling tools is critical for engineering-level planning of EnCs, including technology sizing and operational strategies. The paper combines a review of recent studies with a comparative analysis of selected modelling tools, outlining their capabilities, strengths, and limitations, with a focus on technical capabilities and usability. The findings reveal a growing availability of comprehensive open-source modelling tools, which are well-suited for advanced engineering-level planning of EnCs but require programming skills and expertise in energy system modelling. In contrast, commercial tools offer higher usability and are better suited for feasibility studies. Future development is expected to enhance their representation of demand-side flexibility.