Modelling An Occupancy-Based Hvac System Controller for Building Energy Efficiency
DOI:
https://doi.org/10.15575/gdcs.v61i1.3273Abstract
Heating, Ventilation, and Air Conditioning (HVAC) systems are major energy consumers in commercial buildings, often accounting for nearly half of total energy usage. A primary source of inefficiency is conventional operation that ignores occupancy patterns, leading to unnecessary conditioning of unoccupied spaces. This paper presents a simulation study of an occupancy-based HVAC control system using a simplified first-order thermal model of a building space. Three control strategies are compared: a baseline system without active control, a reactive On-Off controller, and a Proportional-Integral-Derivative (PID) controller tuned using the Ziegler-Nichols method. Both the On-Off and PID controllers are integrated with an occupancy model to enable adaptive operation. Simulation results show that the occupancy-based PID controller achieves the best performance in balancing energy efficiency and thermal comfort compared to the other strategies. In addition, this work highlights a planned extension toward intelligent control methods, such as Deep Reinforcement Learning (DQN), to provide more adaptive and robust HVAC operation in dynamic environments.
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