论文标题
数据科学研究大型食品制冷系统网络的温度概况
Data science to investigate temperature profiles of large networks of food refrigeration systems
论文作者
论文摘要
许多国家的电气发电和传输基础设施都在压力上增加。这部分反映了向低碳经济体的转变,并增加了对可再生发电系统的依赖。传统的化石燃料产生系统的使用减少了,该系统提供了稳定的基本负载,这已被更不可预测的可再生生成所取代。结果,网格上的可用负载变得越来越不稳定。为了应对这种可变性,英国国家电网强调了对各种技术机制的调查(例如,实施智能电网,储能技术,辅助功率来源),当电网有时可能会变得不稳定时,这可能能够防止关键情况。例如,成功实施这些机制可能需要大量电气消费者(例如HVAC系统,食品制冷系统),例如对储能技术(食品冷藏系统)进行额外的投资或将工业过程中的电气需求整合到国家电网(HVAC系统)中。但是,在食品制冷系统的情况下,在这些关键情况下,即使制冷系统中的热惯性在短时间内(例如,1分钟以下)可以在减少系统中的电动输入负载时保持该设备的有效性能,但即使在很短的时间内,这仍然是食品安全的最高风险,即使在很短的时间内(例如,1分钟)(例如,1分钟)。因此,在考虑将来的任何动作(例如投资储能技术)以防止电网变得不稳定时的关键情况之前,还需要在正常使用期间了解这些庞大的食品制冷系统网络中的温度概况如何发展。
The electrical generation and transmission infrastructures of many countries are under increased pressure. This partially reflects the move towards low carbon economies and the increased reliance on renewable power generation systems. There has been a reduction in the use of traditional fossil fuel generation systems, which provide a stable base load, and this has been replaced with more unpredictable renewable generation. As a consequence, the available load on the grid is becoming more unstable. To cope with this variability, the UK National Grid has placed emphasis on the investigation of various technical mechanisms (e.g. implementation of smart grids, energy storage technologies, auxiliary power sources), which may be able to prevent critical situations, when the grid may become sometimes unstable. The successful implementation of these mechanisms may require large numbers of electrical consumers (e.g. HVAC systems, food refrigeration systems) for example to make additional investments in energy storage technologies (food refrigeration systems) or to integrate their electrical demand from industrial processes into the National Grid (HVAC systems). However, in the situation of food refrigeration systems, during these critical situations, even if the thermal inertia within refrigeration systems may maintain effective performance of the device for a short period of time (e.g. under 1 minute) when the electrical input load into the system is reduced, this still carries the paramount risk of food safety even for very short periods of time (e.g. under 1 minute). Therefore before considering any future actions (e.g. investing in energy storage technologies) to prevent the critical situations when grid becomes unstable, it is also needed to understand during the normal use how the temperature profiles evolve along the time inside these massive networks of food refrigeration systems.