Decoupled Step-wise Simulation-based Energy Efficient Control for Industrial Space Cooling: Practical Validation in a Large-Scale Manufacturing Plant

Dezhou Kong, Rabee Reffat, Zhexuan Chen, Zesheng Yang, Haocheng Ma, Dengfeng Du, Zhiang Zhang

Research output: Journal PublicationArticlepeer-review

Abstract

The industrial sector is a predominant contributor to global energy consumption and carbon emissions. In manufacturing plants, district cooling systems account for a large portion of the energy consumption. However, facility operators often lack understanding of the interactions between water-side systems, distribution piping networks, and demand-side systems (air-side systems and production room) due to the complexities of HVAC control management, manufacturing schedules, and heat flow in and around buildings. This results in poor system operation energy efficiency. Specifically, critical control parameters such as chilled water temperature setpoints and equipment sequencing are frequently managed through empirical settings, leading to inefficiencies as the static operation strategy is difficult to adapt to dynamic operating conditions or actual cooling demands. Therefore, this study proposes a decoupled step-wise simulation-based energy-efficient control method as a dynamic adjustment strategy for industrial space air-conditioning. The method establishes and integrates a Modelica-based water-side system model, distribution system model and room thermal response model to dynamically adjust the operation of pumps, and chillers by predicting the status of the demand-side system under different working conditions. Its main advantage lies in the decoupled and step-wise optimization of subsystems, which enhances interpretability, computability and scalability for practical deployment in industrial scenarios. A case study at a large-scale manufacturing plant showed that by applying the dynamic adjustment strategy, this method can contribute to reducing system energy consumption by around 23% during typical cooling seasons compared to the baseline rule-based control, demonstrating the significant potential of the proposed method for improving energy efficiency.
Original languageEnglish
JournalBuilding Simulation
DOIs
Publication statusPublished - 30 Aug 2025

Keywords

  • industrial HVAC
  • optimized control
  • energy efficiency
  • Modelica modeling
  • dynamic adjustment strategy

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