Fit-for-Purpose: Analysis of Occupancy Behaviour Impacts on Intelligent Control Performances in a Nearly Zero Energy Building

The purpose of this paper is to evaluate how different occupancies' conditions affect the performance of building controllers. The study focuses on a nearly zero energy large commercial building with various systems such as boilers, chillers, a building-integrated photovoltaic system, and a combined cooling, heating, and power unit. The building management system incorporates a supervisory genetic algorithm optimization, mid-range controller, and internal controller of equipment using a cascade approach. The mid-range controller is designed using three approaches: 1) proportional-integral-derivative controller tuned by a fuzzy logic system, 2) model predictive controller, and 3) an optimized traditional relay controller. The impacts of occupancies on the controllers are assessed through one factor at a time sensitivity analysis of occupancy density, occupancy activity, and setpoints. The study found that the model predictive controller improved energy efficiency by varying percentages (7% to 85^%) based on occupancy uncertainty, while maintaining a robust thermal comfort performance of around 95% accuracy during different conditions. The PID-fuzzy controller tunes the energy resources to improve energy performance of the building by 15% in accurate modelling, the robustness of its performances in the presence of occupational uncertainty resulting in reducing the impact of occupancies to 5% energy performance gap.