The transition to sustainable energy systems in the face of growing renewable energy adoption and electrification is a complex and critical challenge. The Renewable Energy Hub Optimizer (REHO) emerges as a powerful decision support tool designed to investigate the deployment of energy conversion and storage technologies in this evolving landscape. REHO leverages a Mixed-Integer Linear Programming (MILP) framework combined with a Dantzig-Wolfe decomposition to simultaneously address the optimal design and operation of energy communities, catering to multi-objective considerations across economic, environmental, and efficiency criteria. This paper introduces REHO and highlights its key features and contributions to the field of sustainable energy system planning.