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Simulation and optimization of energy consumption in cold storage chambers from the horticultural industry

The use of industrial cooling for food preservation has been revealed to be an efficient and widely employed technique, from harvest time to final consumption by the customer. However, the most used method to generate that cold (based on the compression refrigeration cycle) requires a considerable amount of electric energy, especially if no appropriate energy efficiency measures are implemented in cold storage chambers. This fact contributes to the increased costs in electricity bills, reduction of competitiveness among companies and also to a negative impact in terms of global warming. To help companies define and implement the right efficiency measures for cold production, this work aims to develop a methodology for simulation and optimization of energy consumption in cold chambers by improving both constructive and operating parameters (external temperature, enclosure insulation, door opening time, etc.), which contribute to the infiltration of heat energy. It is also intended that this methodology determines which of those parameters have greater influence in energy consumptions, as well as to estimate possible savings resulting from the optimization process. Results obtained in a garlic cold chamber showed that it is possible to achieve energy savings of up to 40 % for an initial investment around 1,500 € in efficiency measures and a payback time among 2 and 5 years. On the other hand, parameters that had the greatest influence in energy consumptions were those directly related with thermal insulation of enclosures and entry of warm air within. Total contribution of these two parameters in the global consumption was about 95 %.
- INSTITUTO POLITÉCNICO DE PORTALEGRE Portugal
- INSTITUTO POLITÉCNICO DE PORTALEGRE Portugal
- Instituto Politécnico Nacional Mexico
- Polytechnic Institute of Portalegre Portugal
- INSTITUTO POLITÉCNICO DE PORTALEGRE Portugal
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).12 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
