Dynamic modeling and validation of a liquid desiccant cooling and dehumidification system

Dynamic modeling and validation of a liquid desiccant cooling and dehumidification system In this study, a simplified dynamic model for the liquid desiccant cooling and dehumidification system (LDCDS) is developed from a control viewpoint based on the laws of conservation of energy and mass. The complete LDCDS consists of three subsystems, namely the cooling coil, dehumidifier and cooler in which the models can be estimated separately and combined to obtain the model of LDCDS. The heat and mass transfer rates in model are derived through effectiveness-NTU and hybrid modeling approaches. The parameters of the thermal and moisture dynamic models are pre-identified by using the Levenberg–Marquardt method with static experimental data from the LDCDS pilot plant and then refined by adopting an unscented Kalman filter algorithm with dynamic experimental data. Detailed experimental tests on a pilot plant reveal that the proposed model accurately predicts the system performance under different operating conditions. The proposed model is expected to be applied in further research on the effects of more advanced control and optimization algorithms with the system energy efficiency. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Energy and Buildings Elsevier

Dynamic modeling and validation of a liquid desiccant cooling and dehumidification system

Loading next page...
 
/lp/elsevier/dynamic-modeling-and-validation-of-a-liquid-desiccant-cooling-and-B0BjL1LNGR
Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier B.V.
ISSN
0378-7788
eISSN
1872-6178
D.O.I.
10.1016/j.enbuild.2017.12.041
Publisher site
See Article on Publisher Site

Abstract

In this study, a simplified dynamic model for the liquid desiccant cooling and dehumidification system (LDCDS) is developed from a control viewpoint based on the laws of conservation of energy and mass. The complete LDCDS consists of three subsystems, namely the cooling coil, dehumidifier and cooler in which the models can be estimated separately and combined to obtain the model of LDCDS. The heat and mass transfer rates in model are derived through effectiveness-NTU and hybrid modeling approaches. The parameters of the thermal and moisture dynamic models are pre-identified by using the Levenberg–Marquardt method with static experimental data from the LDCDS pilot plant and then refined by adopting an unscented Kalman filter algorithm with dynamic experimental data. Detailed experimental tests on a pilot plant reveal that the proposed model accurately predicts the system performance under different operating conditions. The proposed model is expected to be applied in further research on the effects of more advanced control and optimization algorithms with the system energy efficiency.

Journal

Energy and BuildingsElsevier

Published: Mar 15, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off