A Comparison Study on Stochastic Modeling Methods for Home Energy Management System

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Obtaining an appropriate model is very crucial to develop an efficient energy management system for the smart home, including photovoltaic (PV) array, plug-in electric vehicle (PEV), home loads, and heat pump (HP). Stochastic modeling methods of smart homes explain random parameters and uncertainties of the aforementioned components. In this paper, a concise yet comprehensive analysis and comparison are presented for these techniques. First, modeling methods are implemented to find appropriate and precise forecasting models for PV, PEV, HP, and home load demand. Then, the accuracy of each model is validated by the real measured data. Finally, the pros and cons of each method are discussed and reviewed. The obtained results show the conditions under which the methods can provide a reliable and accurate description of smart home dynamics.
Original languageEnglish
JournalIEEE Transactions on Industrial Informatics
Volume15
Issue number8
Pages (from-to)4799 - 4808
Number of pages10
ISSN1551-3203
DOIs
Publication statusPublished - Aug 2019

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Energy management systems
Pumps
Hot Temperature
Plug-in electric vehicles

Keywords

  • Comparison
  • Energy management system (EMS)
  • Modeling techniques
  • Smart home
  • Stochastic modeling
  • Uncertainties

Cite this

@article{01e746b0995a45608fdb1847a5c13122,
title = "A Comparison Study on Stochastic Modeling Methods for Home Energy Management System",
abstract = "Obtaining an appropriate model is very crucial to develop an efficient energy management system for the smart home, including photovoltaic (PV) array, plug-in electric vehicle (PEV), home loads, and heat pump (HP). Stochastic modeling methods of smart homes explain random parameters and uncertainties of the aforementioned components. In this paper, a concise yet comprehensive analysis and comparison are presented for these techniques. First, modeling methods are implemented to find appropriate and precise forecasting models for PV, PEV, HP, and home load demand. Then, the accuracy of each model is validated by the real measured data. Finally, the pros and cons of each method are discussed and reviewed. The obtained results show the conditions under which the methods can provide a reliable and accurate description of smart home dynamics.",
keywords = "Comparison, Energy management system (EMS), Modeling techniques, Smart home, Stochastic modeling, Uncertainties",
author = "Mojtaba Yousefi and Amin Hajizadeh and {N. Soltani}, Mohsen",
year = "2019",
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doi = "10.1109/TII.2019.2908431",
language = "English",
volume = "15",
pages = "4799 -- 4808",
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issn = "1551-3203",
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A Comparison Study on Stochastic Modeling Methods for Home Energy Management System. / Yousefi, Mojtaba; Hajizadeh, Amin; N. Soltani, Mohsen.

In: IEEE Transactions on Industrial Informatics, Vol. 15, No. 8, 08.2019, p. 4799 - 4808.

Research output: Contribution to journalJournal articleResearchpeer-review

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AU - Yousefi, Mojtaba

AU - Hajizadeh, Amin

AU - N. Soltani, Mohsen

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Y1 - 2019/8

N2 - Obtaining an appropriate model is very crucial to develop an efficient energy management system for the smart home, including photovoltaic (PV) array, plug-in electric vehicle (PEV), home loads, and heat pump (HP). Stochastic modeling methods of smart homes explain random parameters and uncertainties of the aforementioned components. In this paper, a concise yet comprehensive analysis and comparison are presented for these techniques. First, modeling methods are implemented to find appropriate and precise forecasting models for PV, PEV, HP, and home load demand. Then, the accuracy of each model is validated by the real measured data. Finally, the pros and cons of each method are discussed and reviewed. The obtained results show the conditions under which the methods can provide a reliable and accurate description of smart home dynamics.

AB - Obtaining an appropriate model is very crucial to develop an efficient energy management system for the smart home, including photovoltaic (PV) array, plug-in electric vehicle (PEV), home loads, and heat pump (HP). Stochastic modeling methods of smart homes explain random parameters and uncertainties of the aforementioned components. In this paper, a concise yet comprehensive analysis and comparison are presented for these techniques. First, modeling methods are implemented to find appropriate and precise forecasting models for PV, PEV, HP, and home load demand. Then, the accuracy of each model is validated by the real measured data. Finally, the pros and cons of each method are discussed and reviewed. The obtained results show the conditions under which the methods can provide a reliable and accurate description of smart home dynamics.

KW - Comparison

KW - Energy management system (EMS)

KW - Modeling techniques

KW - Smart home

KW - Stochastic modeling

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