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Grey-box Modeling for System Identification of Household Refrigerators: a Step Toward Smart Appliances

机译:家用冰箱系统辨识的灰盒建模:迈向智能家电的一步

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摘要

This paper presents the grey-box modeling of a vapor-compression refrigeration system for residential applications based on maximum likelihood estimation of parameters in stochastic differential equations. Models obtained are useful in the view of controlling refrigerators as flexible consumption units, which operation can be shifted within temperature and operational constraints. Even if the refrigerators are not intended to be used as smart loads, validated models are useful in predicting units consumption. This information can increase the optimality of the management of other flexible units, such as heat pumps for space heating, in order to smooth the load factor during peak hours, enhance reliability and efficiency in power networks and reduce operational costs.
机译:本文基于随机微分方程中参数的最大似然估计,提出了一种住宅应用蒸汽压缩制冷系统的灰箱模型。所获得的模型在将冰箱作为灵活的消费单位进行控制方面很有用,可以在温度和运行限制范围内改变运行方式。即使不打算将冰箱用作智能负载,经过验证的模型也可用于预测单位能耗。该信息可以提高其他灵活单元(例如用于空间供暖的热泵)的管理的最优性,以使高峰时段的负载系数趋于平稳,提高电网的可靠性和效率并降低运营成本。

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