Energy management of HVAC systems in smart buildings by using fuzzy logic and M2M communication

Building Energy Management Systems provide users with desired environmental conditions by organizing airconditioning and lighting systems. Many studies related to the energy management system in smart buildings have been conducted. However, the thermal comfort of occupants at lower energy consumption is a significant challenge to researchers. Therefore, in this study, a new smart approach is presented, which has the ability to take into account the impact of the next wall neighbors, and the outside temperature to reduce the energy consumption of an HVAC system without affecting the thermal comfort of occupants. Our model is based on four strategies implemented and simulated using the 3D modeling interface of the Rhino/Grasshopper visual programming tool. The control system of our office building intends to meet the ANSI/ASHRAE standard, which defines the thermal comfort of occupants. The proposed system takes into account the effect of different heat loads of a building, such as equipment load, lighting density, and the number of people per area. Our machine-tomachine communication based approach is capable of reducing energy consumption while keeping the occupants thermally comfortable. Consequently, the annual energy consumption has been reduced by an average of 16% at different setpoints of the HVAC system.

Automated summary

A new smart approach is presented in this study to reduce the energy consumption of an HVAC system while maintaining the thermal comfort of occupants by considering the heat loads of a building and implementing machine-to-machine communication. The proposed system has successfully reduced annual energy consumption by an average of 16%.