Abstract
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.
Highlights
Recent reports and perspectives on electricity show a widening gap between electricity generation and electricity demand
The demand for electrical energy is increasing due to the constant increase in the number of devices and systems that consume electrical energy [3]. These conflicting trends lead to an increase in energy costs affecting all economic and social sectors
The energy consumption of chillers is associated with the plant's production capacity
Summary
Recent reports and perspectives on electricity show a widening gap between electricity generation and electricity demand. This contribution proposes a model-based and user-centered approach to automatic energy analysis This approach helps users to reduce their energy costs through automated generation and implementation of individual proposals for optimizing electrical energy for their industrial automation systems [1]. The demand for electrical energy is increasing due to the constant increase in the number of devices and systems that consume electrical energy [3] These conflicting trends lead to an increase in energy costs affecting all economic and social sectors. The growing number and increasing complexity of the systems capture much of the attention of users Additional tasks, such as energy cost analysis, can be overloaded [5]. Improving the energy efficiency of manufacturing processes is one of the top priorities in the sustainable energy hierarchy and is a widely adopted strategy by industry to reduce energy usage, emissions and costs [12]
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