Non-linear Empirical Model for Energy and Thermal Comfort in Buildings

Abstract

Energy consumption in building sector is approximately 40% and is continuously increasing. This is due to the increased living comforts required by the inhabitants within the buildings. Thermal, visual, air quality and humidity are the main comfort parameters within the indoor environment. However, the indoor thermal comfort is core parameter for the inhabitants’ consideration and consumes approximately 30-50% of total building energy consumption. Meanwhile thermal comfort is also challenging for the scientists, researchers and engineers to meet the energy demands of these systems in buildings. In context to that an effort has been made in this paper to develop a non-linear empirical model for energy consumption and thermal comfort. Since, both the objectives are in contradiction and cannot form any direct relationship. However, in linguistic terms these objectives can be described which is so far challenging to drive the behavioral relationship model. Considering this, black box approach of fuzzy inference system map-ping model has been developed. The fuzzy inference mapping system has employed various rule base and membership functions mappings to drive out the most appropriate empirical model function. The developed model function is significant and can be further employed in the optimization of energy and thermal comfort within the buildings.