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

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Abstrakt

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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    Forskningsdatasæt

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

    Kristoffersen, K. C. (Ophavsmand), N. Soltani, M. (Ophavsmand), Hajizadeh, A. (Ophavsmand), Bjørn, P. (Ophavsmand) & Enevoldsen, H. (Ophavsmand), Aalborg University, 26 sep. 2019

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