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

Mojtaba Yousefi; Amin Hajizadeh; Mohsen N. Soltani

doi:10.1109/TII.2019.2908431

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

Mojtaba Yousefi, Amin Hajizadeh, Mohsen N. Soltani

Research output: Contribution to journal › Journal article › Research › peer-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 language	English
Journal	IEEE Transactions on Industrial Informatics
Volume	15
Issue number	8
Pages (from-to)	4799 - 4808
Number of pages	10
ISSN	1551-3203
DOIs	https://doi.org/10.1109/TII.2019.2908431
Publication status	Published - Aug 2019

Keywords

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

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10.1109/TII.2019.2908431

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1 Finished

Energy management in a "smart home" with integrated solar cells, electric vehicles and heat pumps - Energistyring i et ”smart home” med integrerede solceller, elbiler og varmepumper
Hajizadeh, A. & N. Soltani, M.
Elforsk
05/02/2018 → 01/09/2020
Project: Research

1 PhD thesis

Energy Management System for Smart Homes: Modeling, Control, Performance and Profit Assessment
Yousefi, M., 2020, Aalborg Universitetsforlag. 61 p.
Research output: PhD thesis

Open Access
File

Wind-Solar Measurement Database for Renewable Energy Control Laboratory at Aalborg University Esbjerg
Kristoffersen, K. C. (Creator), N. Soltani, M. (Creator), Hajizadeh, A. (Creator), Bjørn, P. (Creator) & Enevoldsen, H. (Creator), Aalborg University, 26 Sept 2019
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Cite this

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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",

month = aug,

doi = "10.1109/TII.2019.2908431",

language = "English",

volume = "15",

pages = "4799 -- 4808",

journal = "IEEE Transactions on Industrial Informatics",

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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

SN - 1551-3203

VL - 15

SP - 4799

EP - 4808

JO - IEEE Transactions on Industrial Informatics

JF - IEEE Transactions on Industrial Informatics

IS - 8

ER -

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

Abstract

Keywords

Access to Document

AUB Link

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Projects

Energy management in a "smart home" with integrated solar cells, electric vehicles and heat pumps - Energistyring i et ”smart home” med integrerede solceller, elbiler og varmepumper

Research output

Energy Management System for Smart Homes: Modeling, Control, Performance and Profit Assessment

Datasets

Wind-Solar Measurement Database for Renewable Energy Control Laboratory at Aalborg University Esbjerg

Cite this