Model for Thermal Comfort and Energy Saving Based on Individual Sensation Estimation

Abstract

In office spaces, the ratio of energy consumption of air conditioning and lighting for maintaining the environment comfort is about 70%. On the other hand, many people claim being dissatisfied with the temperature of the air conditioning. Therefore, there is concern about work efficiency reduction caused by the current air conditioning control. In this research, we propose an automatic control system that improves both energy saving and thermal comfort of all indoor users by quantifying individual differences in thermal comfort from vital information, on the basis of which the optimal settings of both air conditioning and wearable systems that can directly heat and cool individuals are determined. Various environments were simulated with different room sizes, numbers of users in a room, and heating/cooling conditions. The simulation results demonstrated the efficiency of the proposed system for both energy saving and comfort maximization.

Energy Conservation (EC) and Emission Reduction (ER) Technology Based on Genetic Algorithm (GA)

“…Compared with a single effect study, the implementation of carbon tax and carbon emission trading will have many impacts on enterprises in terms of total control, ER cost, technological innovation, ER effect, etc. It is necessary to study it in a unified framework model [9][10].…”

Thermal-Adaptation-Behavior-Based Thermal Sensation Evaluation Model with Surveillance Cameras

“…Furthermore, the presence of individuals and their utilization of equipment have a role in the internal energy consumption and affect the temperature of the environment. The domain of thermal comfort inference has been extensively researched and has garnered significant interest due to its potential to greatly enhance building energy efficiency while ensuring that occupants are satisfied with their interior settings [ 6 , 7 , 8 , 9 ]. Thermal sensation detection algorithms, derived from thermal adaption behaviors seen using a camera, are an innovative and noninvasive means of detecting thermal sensations without the need for further detection equipment [ 10 ].…”