The vertical topologies of HVAC water systems in supertall buildings are one major concern, which yet has been determined in experience-based manners. Therefore, the current article proposes a computational optimization procedure to search optimal design of system topologies, as well as component sizing and control settings. To reduce the computational efforts, the vertical topologies are simplified by considering only major components (e.g., air-handling units, heat exchangers, and chillers).Since both electricity consumption and capital cost are primary concerns for system design, the optimization problem has been solved using a two-objective solver, Nondominated Sorting Genetic Algorithm II. This optimization problem is then validated using a supertall building in Shanghai, and it is concluded that the generated solutions are superior in terms of both electricity consumption and capital cost. Finally, parametric analyses are conducted to provide insight into the uncontrollable variables (i.e., building location, building characteristics) with the hope that system design can be facilitated.
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