Air Conditioning System Energy Saving Diagnosis Method based on Operating Data Research

DOI

10.2991/emcs-16.2016.431How to use a DOI?

Keywords

Conditioning system; The run data; Energy-saving diagnosis; Energy saving potential analysis; Particle swarm optimization algorithm

Abstract

In recent years, in view of existing air conditioning system energy saving diagnosis research has been closely watched. As a typical air conditioning system energy saving diagnosis method, the observation/ac - test/computing - judgment/solution ""(the OTI) method is widely used in the practical project diagnostic analysis, but at the same time, this method also has some shortcomings. This approach requires system based on the actual situation, for example, artificial selection diagnostic index, and then for testing and evaluation. And in the actual process of diagnosis, also need to change, adjust to adapt to the needs of each project. That said, this approach has been limited to a concrete analysis of concrete problems. In recent years, many researchers have been trying to let hair and improve the diagnosis of energy saving, new and old methods, but in terms of existing methods, its essence content is still not beyond the category of the OTI diagnosis methods, so to speak nothing diagnosis method of revolutionary change. System operation data, on the other hand, is the actual air conditioning system running status, the most direct, most real reflection, which run through the automatic monitoring data and take the corresponding optimization to reduce the system energy consumption become an important way to realize the air-conditioning energy saving. At present, many building air conditioning system has been running data acquisition, a large amount of data accumulated in the process of operation for the data analysis system on energy consumption and operation provides the basis. However, a large amount of data also brought ""data disaster"", makes it hard for managers quickly and efficiently find abnormal energy waste and energy consumption problems.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xingzuo Yue
PY  - 2016/01
DA  - 2016/01
TI  - Air Conditioning System Energy Saving Diagnosis Method based on Operating Data Research
BT  - Proceedings of the 2016 International Conference on Education, Management, Computer and Society
PB  - Atlantis Press
SP  - 1721
EP  - 1724
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcs-16.2016.431
DO  - 10.2991/emcs-16.2016.431
ID  - Yue2016/01
ER  -