TY - JOUR
T1 - Coordinated Charge and Discharge Scheduling of Electric Vehicles for Load Curve Shaping
AU - Nimalsiri, Nanduni I.
AU - Ratnam, Elizabeth L.
AU - Smith, David B.
AU - Mediwaththe, Chathurika P.
AU - Halgamuge, Saman K.
N1 - Publisher Copyright:
© 2000-2011 IEEE.
PY - 2022/7
Y1 - 2022/7
N2 - In this paper, we propose two decentralized Electric Vehicle (EV) charge scheduling schemes for shaping the load curve of residential communities connected to the electric grid. The first scheme is designed for Coordinated Valley-Filling (C-VF) of the load curve via only EV charging. The second scheme is designed for Coordinated Valley-Filling and Peak-Shaving (C-VF-PS) of the load curve via both EV charging and discharging. In both schemes, a set of grid-connected EVs referred to as an 'EV Group' (EVG) coordinates their charge (and discharge) schedules by means of an iterative routine. Specifically, at each iteration of the respective routine, each EV in the EVG updates its charge (and discharge) schedule using a water-filling based algorithm that is specifically tailored for load curve shaping. To accommodate heterogeneous EV arrival times, which are often non-deterministic, each of C-VF and C-VF-PS is implemented in two methods, which differ in the way the EVG is formed. The first method requires all the grid-connected EVs to reschedule at designated time intervals, whereas the second method requires each EV to schedule only once, yielding lower computation and communication overheads. Numerical simulation results confirm that, compared to uncoordinated EV charging, C-VF and C-VF-PS reduce the load variance (flattens the load curve) by 47% and 65%, respectively. Furthermore, Method 2 is shown to be more effective than Method 1, in terms of computation and communication overheads.
AB - In this paper, we propose two decentralized Electric Vehicle (EV) charge scheduling schemes for shaping the load curve of residential communities connected to the electric grid. The first scheme is designed for Coordinated Valley-Filling (C-VF) of the load curve via only EV charging. The second scheme is designed for Coordinated Valley-Filling and Peak-Shaving (C-VF-PS) of the load curve via both EV charging and discharging. In both schemes, a set of grid-connected EVs referred to as an 'EV Group' (EVG) coordinates their charge (and discharge) schedules by means of an iterative routine. Specifically, at each iteration of the respective routine, each EV in the EVG updates its charge (and discharge) schedule using a water-filling based algorithm that is specifically tailored for load curve shaping. To accommodate heterogeneous EV arrival times, which are often non-deterministic, each of C-VF and C-VF-PS is implemented in two methods, which differ in the way the EVG is formed. The first method requires all the grid-connected EVs to reschedule at designated time intervals, whereas the second method requires each EV to schedule only once, yielding lower computation and communication overheads. Numerical simulation results confirm that, compared to uncoordinated EV charging, C-VF and C-VF-PS reduce the load variance (flattens the load curve) by 47% and 65%, respectively. Furthermore, Method 2 is shown to be more effective than Method 1, in terms of computation and communication overheads.
KW - Electric vehicle
KW - load curve shaping
KW - peak-shaving
KW - valley-filling
KW - vehicle-to-grid
KW - water-filling
UR - http://www.scopus.com/inward/record.url?scp=85105856889&partnerID=8YFLogxK
U2 - 10.1109/TITS.2021.3071686
DO - 10.1109/TITS.2021.3071686
M3 - Article
AN - SCOPUS:85105856889
SN - 1558-0016
VL - 23
SP - 7653
EP - 7665
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
IS - 7
ER -