APPLICATION OF ADVANCED COMPUTATIONAL TECHNIQUES FOR OPTIMIZING ENERGY EFFICIENCY AND PERFORMANCE IN HVAC SYSTEMS
Keywords:
HVAC systems, computational techniques, energy efficiency, artificial intelligence, machine learning, computational fluid dynamics, optimizationAbstract
Heating, Ventilation, and Air Conditioning (HVAC) systems account for a significant portion of global energy consumption, often exceeding 40% in commercial buildings. Advanced computational techniques, such as artificial intelligence (AI), machine learning (ML), and computational fluid dynamics (CFD), offer immense potential to optimize energy efficiency and performance in HVAC systems. This paper explores state-of-the-art approaches to enhancing HVAC system operation by leveraging data-driven models and simulation-based optimizations. Emphasis is placed on predictive maintenance, energy forecasting, and adaptive control strategies. A review of existing literature and case studies demonstrates significant energy savings—up to 30%—achieved through these advanced techniques. Practical implications, challenges, and future research directions are also discussed.
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