Intelligent System Designs for HVAC Energy Reduction in Buildings: AI-based Forecasting and Hybrid Active/Passive Approaches

Authors

Leena N. Alam, Effat UniversityFollow
Rim M. Obaid, Effat UniversityFollow
Thoraya Musa, Effat UniversityFollow
Wegdan O. AlShateri, Effat UniversityFollow
Passent M. Elkafrawy Prof, Effat UniversityFollow

Abstract

The majority of building energy utilization worldwide is related to HVAC (Heating, Ventilation, and Air-Conditioning) systems. Eighty percent of the energy produced in Saudi Arabia is used by buildings, and since 70\% of that energy is used for ventilation, air conditioning accounts for roughly 50\% of the nation’s electrical use. This study reviewed and compared much research that used various AI-based forecasting algorithms. Specifically, the study explored the potential of passive and active cooling methods and intelligent system designs and used this analysis to develop a hybrid model that combined AI-based forecasting with active/passive approaches for optimal energy savings. The study evaluated the feasibility and cost-effectiveness of an AI- based forecasting model for HVAC energy reduction in Saudi Arabian buildings. The study developed a hybrid model that combined AI-based forecasting with passive and active cooling methods and intelligent system designs for optimal energy savings. Recommendations were provided for implementing and maintaining such a system to contribute to the development of sustainable and energy-efficient buildings and advance the field of AI-based forecasting for HVAC energy reduction.

Recommended Citation

Alam, Leena N.; Obaid, Rim M.; Musa, Thoraya; AlShateri, Wegdan O.; and Elkafrawy, Passent M. Prof (2023) "Intelligent System Designs for HVAC Energy Reduction in Buildings: AI-based Forecasting and Hybrid Active/Passive Approaches," Effat Undergraduate Research Journal: Vol. 4: Iss. 1, Article 3.
Available at: https://digitalcommons.aaru.edu.jo/eurj/vol4/iss1/3