TY - JOUR
T1 - Hierarchical Energy Management System for Home-Energy-Hubs Considering Plug-in Electric Vehicles
AU - Gholinejad, Hamid Reza
AU - Adabi, Jafar
AU - Marzband, Mousa
N1 - Funding information: This work was supported in part by the Babol Noshirvani University of Technology under Grant BNUT/389051/1400 and in part by British Council under Grant IND/CONT/GA/18-19/22.
PY - 2022/9/1
Y1 - 2022/9/1
N2 - 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.
AB - 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.
KW - Electric vehicle (EV)
KW - hierarchical energy management system (HEMS)
KW - home-energy-hub (HEH)
KW - smart charging and discharging
KW - vehicle-To-grid (V2G)
UR - http://www.scopus.com/inward/record.url?scp=85126309005&partnerID=8YFLogxK
U2 - 10.1109/TIA.2022.3158352
DO - 10.1109/TIA.2022.3158352
M3 - Article
SN - 0093-9994
VL - 58
SP - 5582
EP - 5592
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
IS - 5
ER -
