Air-Flow Analysis in Smart Buildings using Fuzzy Logic

Abstract

Building energy management is an emerging area of research with a wide variety of techniques applied in it. During the past few years, there is a huge rise in the demand for energy due to the exponential growth of population. Therefore, progress and development in the field of energy optimization are very necessary. Out of all sectors, residential sector is consuming 40% of energy, and causing 33% of greenhouse gas emission. For the case of residential sector, around 60% of electricity is consumed by the Heating, Ventilation, and Air-Conditioning (HVAC) appliances. This information leads to more precise management of electric devices in the building energy management system. Ventilation is one of the jobs of HVAC system. Ventilation is the strategy of green building that improves indoor air quality, provides better thermal comfort, and strategical ventilation improves energy efficiency. In this research, we have proposed a Fuzzy Inference System (FIS) that manages the state of HVAC system intelligently by creating the synergy of natural ventilation, HVAC system, and building occupancy variations. To create the coordination between natural ventilation and HVAC system, we have considered indoor and outdoor room temperature difference as a driving parameter to control the state of HVAC system and natural ventilation. We have added an additional feature of occupancy mode which is an important criterion to start or stop natural ventilation. The proposed model is assessed using Mamdani and Sugeno FIS. Proposed energy management system provides an intelligent and energy optimized system that efficiently manages the energy consumption and maintains acceptable indoor air quality with the help of different input parameters. The simulation results validated that the energy optimization can be improved by utilization of natural ventilation with the HVAC system by 17%, which led to reduction of electricity bill by 6%.