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proceedings of accelerator conferences held around the world
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| URL | https://doi.org/10.18429/JACoW-ICALEPCS2025-MOCG002 |
|---|---|
| Title | Neural network-based model predictive control for energy efficient HVAC systems for CERN accelerators |
| Authors |
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| Abstract | In times of concern over the environmental impact of high-energy physics organizations, our research in CERN's Cooling and Ventilation group in the Engineering department investigates energy-saving strategies for heating, ventilation, and air conditioning (HVAC) systems. Widely used in both residential and industrial settings, HVAC systems contribute up to 40% of residential and 70% of industrial consumption, making their optimization a global concern. At CERN, cooling and ventilation systems are used to ensure appropriate temperature and humidity conditions in the accelerator complex. Together with general water-cooling systems, these systems account for up to 12% of total electricity consumption of CERN’s flagship accelerator. Despite their energy intensity, these systems are typically managed by classical controllers, which are reliable for temperature and humidity regulation but not optimal in terms of energy efficiency. This study aims to quantify the potential energy savings in HVAC systems using model predictive control (MPC), an advanced control strategy that incorporates behaviour prediction and external data, such as weather forecast. In a quest for a reproducible solution that can be easily adapted to different HVAC plants, the digital twin is built using physics-informed neural networks, following recent advances in academic research. |
| Paper | download: MOCG002.pdf |
| Cite | BibTeX, LaTeX, Text/Word, RIS, EndNote |
| Conference | 20th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS'25) |
| Series | |
| Location | Chicago, IL, USA |
| Date | 20-26 Sep 2025 |
| Publisher | JACoW Publishing, Geneva, Switzerland |
| Editorial Board | Kent Wootton (ANL), Jeffery Biss (FNAL), Gustavo Bruno (ANL), Jeff Kirchman (ANL), Kelly Jaje (ANL), Denise Skiadopoulos (ANL), SuYin Grass Wang (ANL) |
| Online ISBN | 978-3-95450-255-4 |
| Online ISSN | 2226-0358 |
| Received | 06 September 2025 |
| Revised | 20 September 2025 |
| Accepted | 24 October 2025 |
| Issued | 25 November 2025 |
| DOI | 10.18429/JACoW-ICALEPCS2025-MOCG002 |
| Pages | 87-92 |
| Copyright | Published by JACoW Publishing under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s), the published article's title, publisher, and DOI. |