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On the feasibility of model-based design and optimal control of industrial air-conditioning system.

Number: 2382

Author(s) : PARK N., PARK H., KIM S., JIN Z. Q., KWON H., CHO J. M., HWANG Y., OH S.

Summary

This paper concerns the model-based design (MBD) of air-handling unit (AHU) based industrial air conditioning system and its optimal control strategy. It also addresses on why MBD is the best way of overcoming difficulty and complexity in the development of industrial air-conditioning systems by means of field tests or experiments in a psychrometric chamber. In this work, numerical models of AHU components including condensing unit (CDU), heat exchanger coils, desiccant wheels, are integrated to be a hardware-in-the-loop simulation (HILS) system incorporated with a controller hardware. The HILS system constructs a virtual replica, or a digital twin of the AHU system of a battery-separator-film manufacturing factory, the reference site. Validated against measurement data at the reference site, developed virtual system is applied to derive the optimal control strategy for the target evaporating pressures of CDUs with variable speed compressors. For all possible outdoor and return air conditions, candidates of target evaporating pressures are evaluated and weighted under the concept of reinforced learning toward minimal energy cost. It is expected that the best control strategy leads to yearly running cost saving up to 45% as compared to the current simple rule-based control strategy, which leads to 2.9-year payback period for the inverter based CDU systems. The present research demonstrates a digital twin can be a powerful tool to derive the optimal control strategy and achieve maximum energy cost savings for industrial AC systems.

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  • Original title: On the feasibility of model-based design and optimal control of industrial air-conditioning system.
  • Record ID : 30030704
  • Languages: English
  • Subject: Technology
  • Source: 2022 Purdue Conferences. 19th International Refrigeration and Air-Conditioning Conference at Purdue.
  • Publication date: 2022

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