Deep Learning Models for Energy Consumption Prediction and Optimization in HVAC and Ventilation Systems

Prabhu S. Charan

Authors

Prabhu S. Charan Author

Keywords:

HVAC systems, energy consumption prediction, deep learning, optimization, sustainability, neural networks, building management systems

Abstract

Heating, ventilation, and air conditioning (HVAC) systems are among the largest energy consumers in buildings, accounting for nearly 40% of global energy consumption. The increasing demand for energy efficiency and sustainability has motivated the exploration of advanced computational methods to predict and optimize energy consumption. Deep learning (DL) models have emerged as robust tools for capturing complex patterns and providing accurate predictions. This paper explores the application of deep learning techniques in predicting and optimizing energy consumption in HVAC systems. The study provides a comprehensive review of literature, discusses state-of-the-art models, and includes experiments showcasing the effectiveness of DL algorithms. Results highlight the potential of DL for real-time energy optimization, contributing to reduced costs and environmental impact.

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