Iterative reassignment algorithm: Leveraging occupancy based hvac control for improved energy efficiency

Building occupancy significantly impacts HVAC system energy consumption. Occupancy is stochastic in nature, and occupancy from different spaces could be heterogeneous, resulting in heterogeneous distributions of loads, therefore HVAC energy inefficiencies. This paper proposes a framework for conditionally redistributing loads by reassigning occupants at the building level for elevating the effects of occupancy based control, and simulates a real-world office building for validation. Predefined constraints are integrated, and an agglomerate hierarchical clustering-based reassignment algorithm is designed for iteratively assigning occupancy with zone adjacency, orientation, and HVAC layout being considered. Simulation results show that the integration of occupancy based control and occupant reassignment could save up to 9.6% of energy compared to simply applying occupancy based control (18.9% compared to the baseline control that is used in the building. The proposed framework helps reducing unnecessary loads and improves energy efficiency through better-informed decision making for occupancy based HVAC controls.