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Simulation-Assisted Evaluation and Improvement of Guideline 36 for District Cooling Systems: Article No. 118238

  • Pennsylvania State University

Research output: Contribution to journal › Article › peer-review

Abstract

This work systematically evaluates and improves Guideline 36 chilled water controls for district cooling systems (DCSs) using a calibrated and validated simulation-based assessment framework. Guideline 36 is a well-known, sophisticated rule-based control that began including water-cooled chiller plant control sequences for buildings in its 2021 version (G36-2021). These sequences are potentially applicable to DCSs, but few analyses have investigated G36-2021's performance for this application. In this work, G36-2021 is first reviewed extensively, and improvements of the condenser water supply temperature reset logic are proposed. Then, a calibrated modeling testbed of a real-world university DCS is developed to conduct a simulation-based evaluation of G36-2021 with and without improved control sequences. Results from this simulation-based assessment show that as-written G36-2021 control sequences save 8.1% total annual energy and reduce chiller plant equipment runtimes by 20.3% compared to conventional controls. Additionally, the proposed control improvements systematically consume less energy than as-written G36-2021 controls, which is supported by a cross-climate parametric analysis. In summary, this work is the first to quantify Guideline 36's applicability for district energy systems and the first to propose generalizable improvements to its chilled water sequences. To do this, this study develops a simulation-based assessment framework and calibrated, validated modeling testbed to enable rigorous testing and evaluation of advanced district cooling control sequences.
Original languageAmerican English
Number of pages18
JournalEnergy and Buildings
Volume371
DOIs
StatePublished - 2026

NLR Publication Number

  • NLR/JA-5500-100496

Keywords

  • district cooling systems
  • Guideline 36
  • HVAC controls
  • Modelica
  • rule-based controls
  • simulation-based assessment

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