An energy-saving oriented air balancing method for demand controlled ventilation systems with branch and black-box model
Can Cui,
Xin Zhang and
Wenjian Cai
Applied Energy, 2020, vol. 264, issue C, No S0306261920302464
Abstract:
This paper proposes an energy-saving oriented air balancing method based on a branch and black-box (B2) model for multi-zone demand controlled ventilation (DCV) systems. The proposed method can achieve accurate air flow control in each zone, which avoids unnecessary energy consumption caused by over-ventilation. The operating procedures of the proposed method are as follows: Building the B2 model for the DCV system → Predicting the terminal static pressures under the given zone design flow values → Determining the damper angles of each zone based on the static pressure predictions. In the proposed air balancing method, the basic modelling unit is the duct branch, instead of the internal fittings in the previous model-based air balancing method. Therefore, the proposed method does not need to know the complicated fitting information (e.g., elbows, transitions, dampers, etc.,) in its modelling process and therefore becomes much simpler. In addition, the complexity of the proposed B2 model is also greatly reduced since it is independent with the fitting numbers and does not need to calculate the fitting loss coefficients. Furthermore, the radial basis function (RBF) kernel is also utilized in the proposed method to guarantee the air balancing accuracy. Compared with the existing air balancing methods, the proposed method is more efficient and effective in practice. In the lab, the proposed air balancing method was validated on a real DCV system of 5 zones under various design flow conditions. The experimental results verified the effectiveness of the proposed method on both the air balancing control accuracy and the energy saving ability.
Keywords: Demand controlled ventilation system; Over-ventilation; Energy efficiency; Air balancing; Black-box; Radial basis function (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261920302464
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:264:y:2020:i:c:s0306261920302464
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2020.114734
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().