Day-Ahead optimal management of plug-in hybrid electric vehicles in smart homes considering uncertainties
Date
2021-01-30
Embargo
Advisor
Coadvisor
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE
Language
English
Alternative Title
Abstract
The plug-in hybrid electric vehicles (PHEVs) integration into the electrical network introduces new challenges and opportunities for operators and PHEV owners. On the one hand, PHEVs can decrease the environmental pollution. On the other hand, the high penetration of PHEVs in the network without charging management causes harmonics, voltage instability, and increased network problems. In this study, a charging management algorithm is presented to minimize the total cost and flatten the demand curve. The behavior of the PHEV owner in terms of arrival time and leaving time is modeled with a stochastic distribution function. The battery model and hourly power consumption of PHEV are modeled, and the obtained models are applied to determine the battery's state of charge. The proposed method is tested on a sample demand curve with and without a charging management algorithm to verify the efficiency. The results verify the efficiency of the proposed method in decreasing the total cost using the management algorithm for PHEVs, especially when the PHEVs sell the electricity to the network.
Keywords
Energy managemen, Plug-in hybrid electric vehicle, Smart home, Stochastic mode, Uncertainty
Document Type
conferenceObject
Publisher Version
10.1109/PowerTech46648.2021.9495071
Dataset
Citation
Hasankhani, A., Hakimi, S. M., Bodaghi, M., Shafie-khah, M., Osório, G. J., Catalão, J. P. S. (2021). Day-Ahead optimal management of plug-in hybrid electric vehicles in smart homes considering uncertainties. In Proceedings of the IEEE Power Tech 2021 Conference, Madrid, Spain, 28th June-02th July 2021. DOI: 10.1109/PowerTech46648.2021.9495071. Disponível no Repositório UPT, http://hdl.handle.net/11328/3711
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TID
Designation
Access Type
Open Access