Development of optimization technologies for HVAC systems

• Main Author: Govindarajan, Aswini
• Other Authors: Cai Wenjian
• Format: Theses and Dissertations
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/76027
• Institution: Nanyang Technological University

The great demand for the indoor air distribution environment leads to the wide usage of heating, ventilation and cooling (HVAC). Developing optimized automated control strategy is maintain distributed air flow in ventilation system which provides thermal cosiness and proper indoor quality of air. The aim of this thesis is to progress the proficiency of air distribution system by means of commissioning probable automated artificial intelligence-based control strategy. Primarily it focusses on the modelling of physical system and control methodology to improvise the indoor occupancy. Studies of modelling and control strategies are reviewed, and discussed the problem prevails in existing and future solution perspective on HVAC system are investigated. The purpose of designing the novel control strategy for the improvement of air distribution system (ventilation). The proposed controllers used in this method is to integrate the system with cascaded control methodologies. The purpose of using conventional (PID) and artificial intelligence control (Fuzzy logic) to optimize the controller and to improve the response time of the system, eliminate the unwanted disturbances and improves the efficiency. The proposed modelling deals with physical system modelling and it is implemented using MATLAB, Simulink tool called Simscape, physical network system is always considered as a-casual and it enables to create a reusable component which can span the multiple domains in physical system. It solves differential algebraic equations(DAE) which results in accurate simulation results. The main control technology involved in this thesis are conventional PID controller as feedback control and artificial intelligence based fuzzy logic controller as feedforward. The overall simulation results prove the better control accuracy, better output response time which better efficiency and of the system. The simulation results show the indoor air quality (ventilation and air distribution system) improvement is guaranteed.