Model to size a hybrid energy storage system (HESS) based on recurring patterns analysis using DTW clustering and battery oprimization dispatch. This research focuses on the technology-independent sizing methodology of HESS and offers a comprehensive, threefold contribution. Initially, by utilizing dynamic time warpping DTW technique, it clusters similar daily load diagrams and identifies the most recurring pattern. Subsequently, it delve into battery optimization scheduling by using a linear programming (LP) problem, determining an optimal battery dispatch that will serve as input to the next phase. The model then runs a hybridization mathmatical model, crafting a tool that delineates the hybridization area for the optimal HESS sizing.