Multi-Circuit Air-Conditioning System Modelling for Temperature Control

Abstract

The suitable application of innovative control strategies in Heating, Ventilation, and Air-conditioning systems is important to improving the energy efficiency and maintenance of temperature set point to improve thermal comfort in buildings. The increased focus on energy savings and appropriate thermal comfort has resulted in the necessity for more dynamic approach to the use of these controllers. However, the design of these controllers requires the use of an accurate dynamic modelling. Substantial progresses have been made in the past on model development to provide better control strategy to ensure energy savings without sacrificing thermal comfort and indoor air quality in the Heating, Ventilation, and Air-conditioning systems. However, there are scarce model using the data driven approach in the Multi-circuit air-conditioning system. This research, carried out a study on the choice of a dynamic model for an operating centralized multi-circuit water-cooled package unit air-conditioning system using a system identification procedure. Baseline data were collected and analyzed, the model development was achieved by processing, estimating and validating the data in system identification. Result shows that the Autoregressive-moving average with exogenous terms (ARMAX) of the third order model, established the best model structure with the highest Best Fit and Lowest Mean Square Error.

An Efficient HVAC Network Control for Safety Enhancement of a Typical Uninterrupted Power Supply Battery Storage Room

“…The outcomes of the study show that FLC outperforms the traditional PI controllers because it provides a stable response and withstands diverse parameter uncertainties. On another hand, because of the great focus on building energy savings without compromising thermal comfort, Oleolo et al [39] use the system identification method to design a dynamic model for operating a centralized multi-circuit water cooled package unit of HVACS by controlling the temperature. Fiorentini et al [40] propose the design, execution, and practical evaluation of a hybrid model predictive control for a solar-assisted HVACS that has on-site thermal energy generation and storage.…”