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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.
|Journal||IEEE Transactions on Industrial Informatics|
|Pages (from-to)||4799 - 4808|
|Number of pages||10|
|Publication status||Published - Aug 2019|
- Energy management system (EMS)
- Modeling techniques
- Smart home
- Stochastic modeling
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- 1 Finished
- 1 Ph.D. thesis
Energy Management System for Smart Homes: Modeling, Control, Performance and Profit AssessmentYousefi, M., 2020, Aalborg Universitetsforlag. 61 p. (Ph.d.-serien for Det Ingeniør- og Naturvidenskabelige Fakultet, Aalborg Universitet).
Research output: Book/Report › Ph.D. thesisOpen AccessFile
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 Sep 2019