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2025 Vol.32, Issue 3 Preview Page

Research Article

Development and Long-Term Validation of a DNN-Based Cooling Water Temperature Control Algorithm

DNN 기반 냉각수 온도 제어 알고리즘 개발 및 장기 실증 평가

Kyung-Min Kim1
,
Seok-Woo Kim2
,
Chan-Woo Park3
,
Je-Hyeon Lee4*
김 경민1
,
김 석우2
,
박 찬우3
,
이 제헌4*
1Graduate School of Refrigeration and Air-conditioning Engineering, Pukyong National University, Busan, Korea
2B2B Solutions Team, B2B Integrated Offering Center, Samsung Electronics, Korea
3IoT R&D Team, Device Platform Center, Samsung Electronics, Korea
4Department of Refrigeration and Air-conditioning Engineering, Pukyong National University, Busan, Korea
1부경대학교 에너지수송시스템공학부 냉동공조공학전공
2㈜ 삼성전자 B2B 통합오퍼링센터 B2B솔루션팀
3㈜ 삼성전자 디바이스플랫폼센터 IoT 개발팀
4부경대학교 에너지수송시스템공학부 냉동공조공학전공
*Corresponding Author
30 June 2025. pp. 339-347
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Abstract

This study presents the development and field application of a DNN-based control algorithm for optimizing cooling water temperature to reduce cooling energy consumption in an office building. The DNN prediction model was trained using actual operating data and validated in accordance with ASHRAE Guideline 14. An optimization algorithm was then developed to determine the cooling water temperature that minimizes the operating cost of the heat source system, and the algorithm was deployed in the building’s HVAC system. Using 2022 data as the baseline, the algorithm was applied during the 2023 and 2024 cooling seasons, resulting in operating cost reductions of 26.4% and 19.5%, respectively. The findings, based on three years of operational data, demonstrate the effectiveness of the proposed algorithm in achieving energy cost savings under real building conditions.

Keywords
Deep Neural Network(DNN)
Cooling water temperature
Algorithm
Field validation
Energy Cost
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Information
  • Publisher :The Korean Society of Living Environmental System
  • Publisher(Ko) :한국생활환경학회
  • Journal Title :Journal of The Korean Society of Living Environmental System
  • Journal Title(Ko) :한국생활환경학회
  • Volume : 32
  • No :3
  • Pages :339-347
  • Received Date : 2025-05-07
  • Revised Date : 2025-05-21
  • Accepted Date : 2025-05-28
  • DOI :https://doi.org/10.21086/ksles.2025.6.32.3.339
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