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

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Resumé

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.
OriginalsprogEngelsk
TidsskriftIEEE Transactions on Industrial Informatics
Vol/bind15
Udgave nummer8
Sider (fra-til)4799 - 4808
Antal sider10
ISSN1551-3203
DOI
StatusUdgivet - aug. 2019

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Energy management systems
Pumps
Hot Temperature
Plug-in electric vehicles

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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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A Comparison Study on Stochastic Modeling Methods for Home Energy Management System. / Yousefi, Mojtaba; Hajizadeh, Amin; N. Soltani, Mohsen.

I: IEEE Transactions on Industrial Informatics, Bind 15, Nr. 8, 08.2019, s. 4799 - 4808.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

TY - JOUR

T1 - A Comparison Study on Stochastic Modeling Methods for Home Energy Management System

AU - Yousefi, Mojtaba

AU - Hajizadeh, Amin

AU - N. Soltani, Mohsen

PY - 2019/8

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

KW - Uncertainties

U2 - 10.1109/TII.2019.2908431

DO - 10.1109/TII.2019.2908431

M3 - Journal article

VL - 15

SP - 4799

EP - 4808

JO - I E E E Transactions on Industrial Informatics

JF - I E E E Transactions on Industrial Informatics

SN - 1551-3203

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