Thermal energy storage gives a system enhanced operational flexibility because thermal loads can be shifted, not only spatially-from one piece of equipment to another-but also temporally, using storage, from one point in time to another. The resulting optimization problems become non-convex and difficult to solve. This paper illustrates how to take advantage of the enhanced flexibility that storage provides, while simplifying the dynamic optimization problems involved. The optimization strategy presented decouples the static and dynamic pieces of the problem using a hierarchical structure, where a static sub-problem is solved for each trial decision variable in the dynamic problem. Energy savings as high as 9.4 % are observed with cost savings as high as 17.4%.