Issue |
E3S Web Conf.
Volume 57, 2018
2018 3rd International Conference on Sustainable and Renewable Energy Engineering (ICSREE 2018)
|
|
---|---|---|
Article Number | 02002 | |
Number of page(s) | 6 | |
Section | Energy Storage Equipment Optimization and Analysis | |
DOI | https://doi.org/10.1051/e3sconf/20185702002 | |
Published online | 05 October 2018 |
Energy optimization of chillers by automating a Cooling System
1
Departamento de Eléctrica y Electrónica, Universidad de las Fuerzas Armadas ESPE, ID: 60104598, Sangolquí, Ecuador
2
Departamento de Ciencias Exactas, Universidad de las Fuerzas Armadas ESPE, ID: 60104598, Sangolquí, Ecuador
This publication presents the work done on energy optimization of a group of chillers by automating the cooling system of blowing dies in an industry that is entrusted with the manufacture of plastic containers. In a first stage, the preliminary study on the energy analysis of the old system, where each chiller was in charge of cooling a specific group of blow moulding machines, without taking into account whether or not the blow moulding machines are working, is detailed; subsequent to this, the implementation of the automated cooling system was carried out, where all chillers were centralized in a machine room, automation was carried out with a Siemens S7-1200 PLC, switching the chillers on and off is based on the total thermal capacity required by the blow moulding machines. Finally, the energy analysis of the new cooling system was carried out, where the results were compared, and conclusions were drawn.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.