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

Giuseppe Tommaso Costanzo; Fabrizio Sossan; Mattia Marinelli; Peder Bacher; Henrik Madsen

doi:10.1109/IYCE.2013.6604197

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

Giuseppe Tommaso Costanzo, Fabrizio Sossan, Mattia Marinelli, Peder Bacher, Henrik Madsen

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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Abstract

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.

Original language	English
Title of host publication	Proceedings of IEEE 4th International Youth Conference on Energy
Number of pages	5
Publisher	IEEE
Publication date	2013
DOIs	https://doi.org/10.1109/IYCE.2013.6604197
Publication status	Published - 2013
Event	4th International Youth Conference on Energy 2013 - Siofok, Hungary Duration: 6 Jun 2013 → 8 Jun 2013

Conference

Conference	4th International Youth Conference on Energy 2013
Country/Territory	Hungary
City	Siofok
Period	06/06/2013 → 08/06/2013

Keywords

Refrigerators
Stochastic processes
System identification
Load shifting

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

abstract = "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.",

keywords = "Refrigerators, Stochastic processes, System identification, Load shifting",

author = "Costanzo, {Giuseppe Tommaso} and Fabrizio Sossan and Mattia Marinelli and Peder Bacher and Henrik Madsen",

year = "2013",

doi = "10.1109/IYCE.2013.6604197",

language = "English",

booktitle = "Proceedings of IEEE 4th International Youth Conference on Energy",

publisher = "IEEE",

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Grey-box Modeling for System Identification of Household Refrigerators: a Step Toward Smart Appliances. / Costanzo, Giuseppe Tommaso; Sossan, Fabrizio; Marinelli, Mattia et al.
Proceedings of IEEE 4th International Youth Conference on Energy. IEEE, 2013.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Marinelli, Mattia

AU - Bacher, Peder

AU - Madsen, Henrik

PY - 2013

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AB - 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.

KW - Refrigerators

KW - Stochastic processes

KW - System identification

KW - Load shifting

U2 - 10.1109/IYCE.2013.6604197

DO - 10.1109/IYCE.2013.6604197

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Y2 - 6 June 2013 through 8 June 2013

ER -

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

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