Toward an architecture for integrated gas district cooling with data center control to reduce CO2 emission
Gas District Cooling (GDC) provides electricity and chilled water to facilities with relatively low running cost and has the potential to reduce CO2 emission as it can make effective use of wasted energy. However, the present CO2 emission tends to be higher than expected due to the chilled water sup...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Published: |
Elsevier Inc.
2015
|
| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84937514664&doi=10.1016%2fj.suscom.2014.08.010&partnerID=40&md5=3531b02e1f23ce64b9fd63f94c92775e http://eprints.utp.edu.my/26228/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Gas District Cooling (GDC) provides electricity and chilled water to facilities with relatively low running cost and has the potential to reduce CO2 emission as it can make effective use of wasted energy. However, the present CO2 emission tends to be higher than expected due to the chilled water supply-demand gap. To efficiently manage the gap, this paper introduces a novel chilled water supply-demand gap model and proposes an integrated GDC and Data Center (DC) control based on the model. The gap model, defined by GDC plant and DC controllable parameters, estimates the required additional chilled water supply. Then, DC and chillers in the plant are controlled based on the model to minimize the required additional supply. The analysis using GDC operational data in Universiti Teknologi PETRONAS shows that the accuracy of the models depends on temperature differences between rooms and outdoor, and Steam Absorption Chillers (SAC) operations. Thus, the analysis suggests that the incorporation of room and outdoor temperature sensors in the DC, and the proper scheduling of SAC operation can improve the accuracy of the models. The improved accuracy will in turn allows the GDC operation to be better optimized, resulting in a reduced CO2 emission. © 2014 Elsevier Inc. All rights reserved. |
|---|