Multi-circuit air-conditioning system modelling for temperature control

The suitable application of innovative control strategies in Heating, Ventilation, and Airconditioning 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 therm...

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Bibliographic Details
Main Authors: Oleolo, Ibrahim, Abdullah, Hayati, Mohamad, Maziah, Mohd. Jaafar, Mohammad Nazri, Baharain, Akmal, Sulaiman, Sapiah
Format: Article
Language:English
Published: Penerbit Akademia Baru 2021
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Online Access:http://eprints.utm.my/id/eprint/93968/1/HayatiAbdullah2021_MultiCircuitAirConditioningSystem.pdf
http://eprints.utm.my/id/eprint/93968/
http://dx.doi.org/10.37934/arfmts.83.2.1424
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Summary:The suitable application of innovative control strategies in Heating, Ventilation, and Airconditioning 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.