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Hierarchical Energy Management System for Home-Energy-Hubs Considering Plug-In Electric Vehicles.

Authors :
Gholinejad, Hamid Reza
Adabi, Jafar
Marzband, Mousa
Source :
IEEE Transactions on Industry Applications. Sep/Oct2022, Vol. 58 Issue 5, p5582-5592. 11p.
Publication Year :
2022

Abstract

The escalating demand on electric vehicles (EVs) has enhanced the necessity of adequate charging infrastructure, especially in residential areas. This article proposes a smart charging approach for off-board EVs chargers in home-energy-hub (HEH) applications along with dc sources such as photovoltaic and battery storage (BS). The proposed method facilitates smart charging and discharging of EVs to obtain both vehicle-to-x and x-to-vehicle operations focusing on the domestic applications integrated with renewable and storage elements. Furthermore, the optimal state-of-charge (SOC) profiles for BS and EV in the HEHs system is defined by the extended Bellman-Ford-Moor algorithm (BFMA). This modified BFMA utilizes the forecasted data such as solar irradiation, electricity tariff, and power consumption to gain economic benefits in HEHs with respect to the user and EV requirements. Moreover, the plugging time, duration, and initial/final SOC are fluctuating at each connection due to the stochastic nature of EV conditions and user settings. This study presents a laboratory implementation of two-level hierarchical energy management system for HEHs with plug-in electric vehicles. In fact, the primary level includes power converters controller, while the proposed algorithm is implemented in the secondary level. Finally, the simulation and experimental results confirm the effectiveness of the proposed analysis regarding the interaction of HEHs and power grid with EVs behavior. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00939994
Volume :
58
Issue :
5
Database :
Academic Search Index
Journal :
IEEE Transactions on Industry Applications
Publication Type :
Academic Journal
Accession number :
160651506
Full Text :
https://doi.org/10.1109/TIA.2022.3158352