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Even though energy efficient climate control of buildings using modelpredictive control (MPC) has been widely investigated, most MPC formulationsignore humidity and latent heat. The inclusion of moisture makes the problemconsiderably more challenging, primarily since a cooling and dehumidifying coilmodel which accounts for both sensible and latent heat transfers is needed. Inthis work, we propose an MPC controller in which humidity and latent heat areincorporated in a principled manner. We construct low order data-driven modelsof a cooling and dehumidifying coil that can be used in the MPC formulation.The resulting controller's performance is tested in simulation using a plantthat differs significantly from the model used by the optimizer. Additionally,the performance of the proposed controller is compared with that of a naive MPCcontroller which does not explicitly consider humidity, and also to that of aconventional rule-based controller. Simulations show that the proposed MPCcontroller outperforms the other two consistently. It is also observed that thenaive MPC formulation which does not consider humidity leads to poor humiditycontrol under certain conditions. Such violations in humidity can adverselyaffect occupant comfort and health.

MPC for Energy Efficient HVAC Control with Humidity and Latent Heat Considerations