Development of Economizer Control Method with Variable Mixed Air Temperature

Jin-Hyun Lee, Yong-Shik Kim, Jae-Hun Jo, Hyun Cho and Young-Hum Cho
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Jin-Hyun Lee: Department of Architectural Engineering, Graduate School of Yeungnam University, Gyeongsan 38541, Korea
Yong-Shik Kim: Division of Architecture and Urban Planning, Incheon National University, Incheon 22012, Korea
Jae-Hun Jo: Division of Architecture, Inha University, Incheon 22212, Korea
Hyun Cho: R&D Center, POSCO E&C, Incheon 22009, Korea
Young-Hum Cho: School of Architecture, Yeungnam University, Gyeongsan 38541, Korea

Energies, 2018, vol. 11, issue 9, 1-18

Abstract: Achieving energy efficiency by improving the operating method of the system used in existing buildings is attracting considerable attention. The Building Design Criteria for Energy Saving was established to induce energy saving design in the domestic construction field, and the introduction of a free-cooling system, such as an economizer system, as an item of the mechanical sector, was evaluated. The economizer is an energy saving method that reduces the building load by introducing outdoor air through damper control according to the indoor and outdoor conditions. The system consists of dry-bulb temperature control and enthalpy control and the mixed air temperature is kept constant in the conventional economizer controls. On the other hand, in dry-bulb temperature control, when the set value of the mixed air temperature is changed according to the load, additional energy savings are expected compared to the conventional control method. Therefore, this paper proposes an economizer control that makes the mixed air temperature variable according to the load in a Constant Air Volume single duct system. For this, a load prediction is needed and an Artificial Neural Network is used for the load prediction. In addition, the relationship between the mixed air temperature and energy were analyzed using the BIN method and TRNSYS 17. Based on the results of previous analysis, a control method which predicting the load using Artificial Neural Network and controlling the mixed air temperature according to the predicted load in the dry-bulb temperature control of a Constant Air Volume single duct system is proposed and the proposed control was applied to the dynamic simulation program and compared with the conventional control. The results show that the temperature of each room was 21–23 °C in summer and 22.5–26 °C in winter when the economizer was controlled using the proposed control method and the energy consumption analysis showed that 19% of the energy was reduced compared to the conventional method when the proposed method was controlled.

Keywords: economizer; mixed air temperature; Constant Air Volume single duct system; Artificial Neural Network (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
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