A Simulation-Based Study of Model Predictive Control in a Medium-Sized Commercial Building

摘要

This paper presents a computationally efficient model predictive control (MPC) algorithm to optimize the energyrnuse of the heating ventilation, and air-conditioning (HVAC) system in a multi-zone building and demonstrates thernbenefits using whole building energy simulations. High-fidelity models are often not well suited for optimizationbasedrncontroller design and implementation. In this paper, we present an MPC algorithm using data-driven modelsrnto optimize the energy consumption of a multi-zone building served by multiple air handling units (AHUs) and arncentral chiller plant. The simulation results show promising benefits of applying the MPC algorithm with an averagernenergy saving of 15% for cooling season. The computational efficiency of the MPC algorithm demonstrated makesrnit suitable for real-time implementation planned in the near future.