TY - JOUR
T1 - Routing and Charging Facility Location for EVs under Nodal Pricing of Electricity
T2 - A Bilevel Model Solved Using Special Ordered Set
AU - Gonzalez, Sebastian
AU - Feijoo, Felipe
AU - Basso, Franco
AU - Subramanian, Vignesh
AU - Sankaranarayanan, Sriram
AU - Das, Tapas K.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - We consider the problem of identifying optimal location of electric vehicle (EV) charging stations, while accounting for (i) route optimization and (ii) charging cost optimization by the EV fleets, where the electricity price is obtained endogenously by an optimal power flow (OPF) model. We solve the problem using a bi-objective bilevel programming framework with the objectives being one of minimising travel time and the other of minimising EV charging cost. The upper level problem consists of the facility location and the transportation model and the lower level problem consists of the OPF model. After reformulating this computational hard problem as a mathematical program with equilibrium constraints (MPEC), we solve the problem using a special ordered sets-type 1 (SOS1)-based approach. We record the significant improvement in speed by our method, as opposed to the standard Big-M approach. Finally, we apply the technique to the Sioux Falls transportation network with the IEEE 14-bus electricity network embedded on it. We observe that solutions through our models results in as much 37% lower operating costs for the EVs.
AB - We consider the problem of identifying optimal location of electric vehicle (EV) charging stations, while accounting for (i) route optimization and (ii) charging cost optimization by the EV fleets, where the electricity price is obtained endogenously by an optimal power flow (OPF) model. We solve the problem using a bi-objective bilevel programming framework with the objectives being one of minimising travel time and the other of minimising EV charging cost. The upper level problem consists of the facility location and the transportation model and the lower level problem consists of the OPF model. After reformulating this computational hard problem as a mathematical program with equilibrium constraints (MPEC), we solve the problem using a special ordered sets-type 1 (SOS1)-based approach. We record the significant improvement in speed by our method, as opposed to the standard Big-M approach. Finally, we apply the technique to the Sioux Falls transportation network with the IEEE 14-bus electricity network embedded on it. We observe that solutions through our models results in as much 37% lower operating costs for the EVs.
KW - Bilevel model
KW - EV transportation network
KW - charging facility
KW - electricity network
KW - special ordered set-type1 (SOS1)
UR - http://www.scopus.com/inward/record.url?scp=85126674018&partnerID=8YFLogxK
U2 - 10.1109/TSG.2022.3159603
DO - 10.1109/TSG.2022.3159603
M3 - Article
AN - SCOPUS:85126674018
SN - 1949-3053
VL - 13
SP - 3059
EP - 3068
JO - IEEE Transactions on Smart Grid
JF - IEEE Transactions on Smart Grid
IS - 4
ER -