TY - GEN
T1 - Solar-Powered Vehicle-to-Load (V2L) Plug-in Electric Vehicles: Alleviation of the Photovoltaic Power Decay
AU - Antoniadis, Charalampos
AU - Ghazzai, Hakim
AU - Massoud, Yehia Mahmoud
N1 - KAUST Repository Item: Exported on 2023-05-09
PY - 2023/5/3
Y1 - 2023/5/3
N2 - As any alternating current (AC) load, plug-in electric vehicle (PEV) battery when powered by a photovoltaic (PV) source is subject to the power decay problem. To optimize the PV power extraction for a given non-uniform irradiance and temperature, the PV power must be managed by a maximum power extraction (MPE) system. The PV MPE coupled with an inverter and a PEV battery includes a proportional integral (PI) control system which negatively impacts the MPE controller performance. This is unlike a straightforward MPE system without a PI control where the PV power is exclusively controlled by the MPE controller. Metaheuristic algorithms are usually employed to optimize the PV MPE systems for a non-PI controlled MPE system, This study proposes a low exploration metaheuristic-based algorithm to mitigate the problems with the MPE system coupled with a PI control system. The proposed algorithm is contrasted with the low burden narrow search (LBNS) (low exploration) and the Jaya algorithms (high exploration). The findings show that the proposed algorithm performed significantly better than LBNS and Jaya in addressing the aforementioned problems.
AB - As any alternating current (AC) load, plug-in electric vehicle (PEV) battery when powered by a photovoltaic (PV) source is subject to the power decay problem. To optimize the PV power extraction for a given non-uniform irradiance and temperature, the PV power must be managed by a maximum power extraction (MPE) system. The PV MPE coupled with an inverter and a PEV battery includes a proportional integral (PI) control system which negatively impacts the MPE controller performance. This is unlike a straightforward MPE system without a PI control where the PV power is exclusively controlled by the MPE controller. Metaheuristic algorithms are usually employed to optimize the PV MPE systems for a non-PI controlled MPE system, This study proposes a low exploration metaheuristic-based algorithm to mitigate the problems with the MPE system coupled with a PI control system. The proposed algorithm is contrasted with the low burden narrow search (LBNS) (low exploration) and the Jaya algorithms (high exploration). The findings show that the proposed algorithm performed significantly better than LBNS and Jaya in addressing the aforementioned problems.
UR - http://hdl.handle.net/10754/691562
UR - https://ieeexplore.ieee.org/document/10112517/
U2 - 10.1109/sm57895.2023.10112517
DO - 10.1109/sm57895.2023.10112517
M3 - Conference contribution
BT - 2023 IEEE International Conference on Smart Mobility (SM)
PB - IEEE
ER -
