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Title: Lower and upper threshold limit for artificial neural network based chilled and condenser water temperatures set-point control in a chilled water system

Journal Article · · Energy Reports
 [1];  [2];  [1];  [3];  [4];  [5];  [6];  [1]
  1. Korea Univ., Seoul, (Korea, Republic of)
  2. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
  3. Pukyong National Univ., Busan (Korea, Republic of)
  4. Samsung LED, R&D Inst., Suwon (Korea, Republic of)
  5. Gachon Univ., Sungnam (Korea, Republic of)
  6. Hanbat National Univ., Daejeon (Korea, Republic of)
+ Show Author Affiliations

In this study, an ANN (artificial neural network) based real-time optimized control algorithm for a chilled water cooling system was developed and applied in an actual building to analyze its cooling energy saving effects through in-situ application and actual measurements. For this purpose, the cooling tower’s CndWT (condenser water temperature) and the chiller’s ChWT (chilled water temperature) were set as system control variables. To evaluate algorithm performance, the electric consumption and the COP (coefficient of performance) were compared and analyzed when ChWT and CndWTs were controlled conventionally and controlled based on the ANN. During the analysis, unexpected abnormal data was observed due to insufficient training data and limited consideration of OWBT (outdoor air wet-bulb temperature) when determining the CndWT set-point. Therefore, it is necessary to further build training data from a wider range of conditions and to set the lower limit of CndWT set-point to at least +3.6 °C above OWBT when the OWBT is higher than 23 °C, so that further energy savings can be achieved.

Research Organization:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE)
Grant/Contract Number:
AC05-00OR22725
OSTI ID:
2007706
Journal Information:
Energy Reports, Vol. 9; ISSN 2352-4847
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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Related Subjects

42 ENGINEERING
ANN (Artificial neural network)
ChWT (Chilled water temperature)
CndWT (Condenser water temperature)
in-situ application
OWBT (outdoor air wet-bulb temperature)