Optimizing VRF System Operation for Energy Efficiency under Power Constraints: On-Site Experiment

This paper proposes an approach to minimize the overall energy consumption of variable refrigerant flow (VRF) heating and cooling systems. VRF systems with uncoordinated load scheduling result in a significant power imbalance and a sudden increase in energy consumption. The proposed coordinated load scheduling for VRF systems addresses the issue while guaranteeing the thermal comfort of occupant with peak power constraints. This work uses mixed integer linear programming and model predictive control (MPC). Our on-site experimental results highlight our proposed approach reduces total energy consumption by 2.4 kWh (27.5%) on average while satisfying thermal comfort over a rule-based control one.