The application of Artificial intelligence to control the energy consumption of Air Conditioner

Abstract

Sustainable and energy-efficient buildings have become increasingly essential in light of growing environmental concerns and rising energy costs, with the building sector recognized as one of the largest energy consumers globally. Heating, Ventilation, and Air Conditioning (HVAC) systems alone can account for up to 50% of a building’s total energy consumption, making the optimization of their performance a critical strategy for reducing both environmental impact and operational expenses. This study investigates the influence of varying levels of thermal insulation and HVAC system efficiencies on cooling energy consumption using a simulation-based analysis platform developed in a laboratory at the University of Abou Bekr Belkaid in Tlemcen. The analysis was structured around two scenarios: S1 (Midea MSAGB-12HRN1-Q) and S2 (LG S09EQ.NSJ). In the first scenario, the calculated change in energy consumption between the two cases was -1.4%, indicating no actual energy savings in the second case. Similarly, in the second scenario, the difference was -1.2%, again demonstrating the absence of meaningful savings. Overall, the total energy consumption in the first scenario was higher than in the second, primarily due to the superior performance of the LG unit, which is an inverter-type air conditioner with higher efficiency. These findings highlight the combined importance of high-quality thermal insulation and advanced HVAC system technologies in achieving significant reductions in cooling energy demand.