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Factors causing peak energy consumption of reefers at container terminals

机译:导致集装箱码头峰值能量消耗的因素

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Reefers are refrigerated containers commonly used for transporting perishable goods such as meat, fish, vegetables and fruit. Nowadays, reefers are responsible for 40% of the total energy consumption of container terminals, when connected to the electricity grid on shore. Every time when a large number of reefers is plugged-in after arrival, peaks in energy consumption occur. As container terminals purchase energy using a demand-based fee, exceeding the reserved capacity during peak times increases the energy costs of the terminal significantly. So far the literature has not dealt with the root causes of peak energy consumption of reefers, or ways to reduce these peaks. The aim of this paper is to identify the root causes and to quantify their importance. We use data of energy consumption of reefers at a large container terminal, over the period of 1 year. In order to identify the importance of factors, we apply a sequential multiple regression analysis approach with backwards feature selection. Variations in energy demand are explained for 77% by the arrival pattern of containers, for about 5% by dwell time and for 2% by other factors, such as container temperature at plug-in. Promising approaches to reduce peak energy consumption of reefers includes dynamic pricing, energy management and specific peak shaving strategies.
机译:Refers是用于运输易腐货物,如肉类,鱼类,蔬菜和水果的冷藏容器。如今,当连接到岸上的电网时,Refers负责集装箱码头的总能耗的40%。每次在到达后插入大量的refers时,会发生能量消耗的峰值。随着集装箱码头使用基于需求的费用购买能源,在高峰期期间超过预留容量会显着提高终端的能源成本。到目前为止,文献尚未处理峰值能量消耗的根本原因,或减少这些峰的方法。本文的目的是识别根本原因并量化它们的重要性。我们在1年的时间内使用大型集装箱码头的refefers的能耗数据。为了确定因素的重要性,我们使用向后特征选择应用一份顺序多元回归分析方法。通过容器的到达模式解释了能量需求的变化,通过容器的到来模式,约5%通过停留时间和2%的其他因素,例如插入时的容器温度。有希望的降低峰值能耗的方法包括动态定价,能源管理和特定的峰值剃须策略。

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