OPTIMIZATION OF HVAC ENERGY CONSUMPTION UNDER UNCERTAINTY OF EXTERNAL CONDITIONS: A PROBABILISTIC MODELING APPROACH
Keywords:
HVAC systems;, energy optimization;, uncertainty modeling;, probabilistic approach;, stochastic control;, occupancy prediction;, weather variability.Abstract
Abstract: Heating, Ventilation, and Air Conditioning (HVAC) systems account for about 40% of building energy use. Their performance is strongly affected by uncertain external factors such as weather and stochastic occupancy, limiting deterministic control strategies. This study proposes a probabilistic optimization framework for HVAC management, modeling occupancy as a stochastic process and weather via probability distributions. Indoor temperature and CO₂ dynamics are described by stochastic differential equations within a constrained optimization problem. A stochastic Model Predictive Control (MPC) with Monte Carlo sampling is applied, achieving 10–15% expected energy savings and improved comfort reliability, especially in educational and office buildings.
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Copyright (c) 2025 Mohira Rahimova, Lyudmila Varlamova
This work is licensed under a Creative Commons Attribution 4.0 International License.
