Improving the Predeveloped Local Ecology: Maximizing Condensate Collection through Strategic Building Operation

This work demonstrates how a water and energy sustainable building’s heating, ventilation, and air conditioning (HVAC) system may be operated to maximize condensate production while upholding user thermal comfort and energy consumption requirements. A physics-based HVAC condensate model was presented and validated against operating data from the Kendeda Building for Innovative Sustainable Design (KBISD), a $\mathrm{3,437.4}\text{-}{\mathrm{m}}^2$ ($\mathrm{37,000}\text{-}{\mathrm{ft}}^2$) academic building on the Georgia Institute of Technology’s Atlanta campus. A sensitivity study of the HVAC condensate production and power consumption was performed. Metamodels were developed to concisely yet accurately represent the physics-based model, and these were used as the basis of an optimization exercise to identify competitive operating conditions for maximizing condensate production. The case studies included here found optimized HVAC system operation strategies to produce up to 708% more condensate. The demonstrated approach may be reproduced by system operators or building automation systems to increase condensate production without sacrificing building system-level energy and thermal comfort requirements.

This work demonstrates how a building’s heating, ventilation, and air conditioning (HVAC) system may be operated to increase the amount of water, or condensate, which may be pulled out of the air and collected. A simple engineering model is presented and verified against real-world data. This is used as the basis for an optimization approach that allows operators to make strategic, mathematically substantiated decisions to impact the amount of condensate collected and the power required to do so. In addition, the use of so-called metamodels for reducing complex engineering models or systems into simple mathematical representations is exemplified for increasing the speed of the analyses performed in this work. These metamodels may be used to represent HVAC or other building systems and allow for optimization efforts similar to those presented herein or potentially model predictive control. The case studies discussed in this work bring the optimization approach and metamodels together to demonstrate how a building may theoretically be operated to increase its condensate production by 708% within reasonable power requirements and without sacrificing the comfort of the building’s occupants.